# Precision Oncology, Cell Signaling and Targeted Therapy: A Holistic Approach to Molecular Cancer Therapeutics

Manish Kumar

► To cite this version:

Manish Kumar. Precision Oncology, Cell Signaling and Targeted Therapy: A Holistic Approach to Molecular Cancer Therapeutics. 2024, 10.17632/cm276ydxwj.2. hal-04568944

HAL Id: hal-04568944

https://hal.science/hal-04568944

Submitted on 17 May 2024

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<figure><img src="image_1.png" /></figure>
# Precision Oncology, Cell Signaling and Targeted Therapy: A Holistic Approach to Molecular Cancer Therapeutics

Manish Kumar

► To cite this version:

Manish Kumar. Precision Oncology, Cell Signaling and Targeted Therapy: A Holistic Approach to Molecular Cancer Therapeutics. 2024, 10.17632/cm276ydxwj.2. hal-04568944

HAL Id: hal-04568944

https://hal.science/hal-04568944v1

Submitted on 17 May 2024

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>
**Manish Kumar**

School of Bio Sciences & Technology
Vellore Institute of Technology, Vellore, Tamil Nadu, India

**Email:** kmanish125@yahoo.com, kmanish.bt125@gmail.com

ORCID: https://orcid.org/0000-0002-6021-7063

CORRESPONDENCE

1.
C/O. Sri M. Narayan Swami
7/1A, 1st Street, Bhavani Nagar
Katpadi P.O. Dharapadavedu,
Vellore- 632007, Tamil Nadu, India

2.
ME-010-0017, Dhruvneeti Colony
Near Samarpan Hospital, Rajneeti Road
Madhopur, P.O. Basudeopur
Munger- 811202, Bihar, India

**Abstract:** Cancer is a fatal genetic disease with different aspects of complexity, including cancer immune evasion, treatment resistance and recurrence, requiring optimized treatment for proper cure. Molecular studies have revealed that tumors are hugely heterogeneous in nature, leading to the complexity of cancer progression that is ultimately linked to its genetic machinery. In recent decades, there has been a deluge in the large-scale production of anticancer agents, primarily due to advances in genomic technologies enabling precise targeting of oncogenic pathways involved in disease development. It is important to note that patients with the same types of cancer respond differently to cancer treatments, indicating the need for patient-specific treatment options. An in-depth genomic study of tumors will be needed to fully understand the driving factors of cancer initiation and progression for effective targeted therapy. Precision oncology has evolved as a form of cancer therapy focused on genetic profiling of patients’ tumors to identify molecular alterations involved in cancer manifestation for tailored individualized treatment of the disease. This article aims to briefly explain the foundations and frontiers of precision oncology and review the tools and techniques involved in the process to assess its scope and importance in achieving effective cures against cancer.

**Keywords:** Gene Mutation; Cancer Genomics; Targeted Therapy; Immunotherapy, Precision Medicine
**Manish Kumar**

School of Bio Sciences & Technology
Vellore Institute of Technology, Vellore, Tamil Nadu, India

**Email:** kmanish125@yahoo.com, kmanish.bt125@gmail.com

ORCID: https://orcid.org/0000-0002-6021-7063

CORRESPONDENCE

1.
C/O. Sri M. Narayan Swami
7/1A, 1st Street, Bhavani Nagar
Katpadi P.O. Dharapadavedu,
Vellore- 632007, Tamil Nadu, India

2.
ME-010-0017, Dhruvneeti Colony
Near Samarpan Hospital, Rajneeti Road
Madhopur, P.O. Basudeopur
Munger- 811202, Bihar, India

**Abstract:** Cancer is a fatal genetic disease with different aspects of complexity, including cancer immune evasion, treatment resistance and recurrence, requiring optimized treatment for proper cure. Molecular studies have revealed that tumors are hugely heterogeneous in nature, leading to the complexity of cancer progression that is ultimately linked to its genetic machinery. In recent decades, there has been a deluge in the large-scale production of anticancer agents, primarily due to advances in genomic technologies enabling precise targeting of oncogenic pathways involved in disease development. It is important to note that patients with the same types of cancer respond differently to cancer treatments, indicating the need for patient-specific treatment options. An in-depth genomic study of tumors will be needed to fully understand the driving factors of cancer initiation and progression for effective targeted therapy. Precision oncology has evolved as a form of cancer therapy focused on genetic profiling of patients’ tumors to identify molecular alterations involved in cancer manifestation for tailored individualized treatment of the disease. This article aims to briefly explain the foundations and frontiers of precision oncology and review the tools and techniques involved in the process to assess its scope and importance in achieving effective cures against cancer.

**Keywords:** Gene Mutation; Cancer Genomics; Targeted Therapy; Immunotherapy, Precision Medicine
# 1. Introduction

Cancer is one of the leading causes of death worldwide. It is considered that genetic factors and epigenetic changes allow cells to proliferate in an uncontrolled manner by escaping essential regulatory mechanisms. Rigorous cancer research in the past few decades supported by advances in cell and molecular biology has led scientists to clearly understand there are genetic changes associated with cancer incidences that cause the disease to grow and spread to other parts of the body. Cancer is initiated as the result of uncontrolled cell division and proliferation leading to tumor formation which culminates in metastasis that involves the dissemination of tumor cells to new sites in the body forming secondary tumors, and is responsible for about 90% of cancer-related deaths in reality. Cell proliferation requires a balanced rate of cell growth and division to maintain the increase in cell numbers for growth and development, maintenance of tissue homeostasis and wound healing. Cancer progression is frequently associated with increased cell proliferation, metabolic dysregulation, resistance to apoptosis, genetic instability, initiation of angiogenesis, invasion and increased migration of cells. Genetic changes appearing in the information system of cells that program its unregulated growth and proliferation gradually lead to the manifestation of cancer and therapeutic options must be directed accordingly [1]. The critical roles played by some of the molecules associated with specific oncogenic pathways and the cellular microenvironment that lead to cancer progression and metastasis have been precisely described in recent years based on findings from the Human Genome Project. New developments in DNA and RNA analysis have made it possible to study underlying genetic changes systematically. These advances have allowed researchers to have a more in-depth understanding of the signaling pathways and processes involved, in carcinogenesis and have led to the identification of critical pathways that can be successfully targeted for therapeutic purposes [2]. Importantly, epidemiological studies have consistently shown that environmental factors or lifestyle changes involving mutagenic agents are the primary culprits. Thus, it is not only necessary to associate genetic mutations with different cancers but also to work on the mechanism of action of mutagens by focusing on enzymes which could invariably mediate oncogenic transformations. For example, overexpression of the ribonucleotide reductase (RnR) enzyme which catalyzes the formation of deoxyribonucleotides from ribonucleotides necessary for cell division, is implicated in many forms of cancer and the genes for the components of the enzyme are often mutated, leading to hyperactivity of the enzyme. But there are instances indicating that cytoplasmic material rather than the karyoplast would be responsible for cellular transformation that might be better explained as a consequence of certain epigenetic modulation than purely genetic changes. RnR active site inhibitors have been developed to biophysically deactivate the enzyme when necessary, with positive results [3].

Over the years, technological advances in the field of molecular biology have been exploited to unravel genetic and epigenetic changes to fully understand the pathogenesis of human cancer. The range of cancer-causing mutations is known to be huge, and the mutational landscape differs from one another depending on the type of cancer and even people suffering from the same cancer type are found to have considerably different mutation patterns. Moreover, it has long been observed that every patient responds differently to particular treatments despite having the same type and stage of cancer. These observations have been compelling and led researchers to adopt a precision medicine approach to cancer therapy necessitating the study of genetic features of vulnerable individuals for a patient-specific treatment regimen towards the most effective treatment of cancer. Precision oncology has evolved as a form of cancer therapy focused on genetic profiling of tumors to identify molecular alterations involved in cancer development for tailored individualized treatment of the disease [4,5]. The emergence of next-generation sequencing (NGS) in 2005 has proved to be massively important in this direction as the technology is used to determine the order of nucleotides in entire genomes or targeted regions of DNA or RNA and has revolutionized biological research, allowing scientists to study biological systems at a level never tried before. It can provide new insights into the nature of genes and proteins thought to be associated with cancer, and the application of evolving molecular techniques to the study of cancer has also provided markers that have led to new advances in tumor diagnosis, prognosis, and treatment which have proven to be immensely helpful in advancing precision oncology [6].

Cancer development generally is a multi-step process triggered by mutations leading to the activation of specific oncogenic pathways with the concurrent inactivation of tumor suppressor genes that act as sentinels to control unwanted cell growth, proliferation, tumor microenvironment (TME) remodeling, epithelial to
# 1. Introduction

Cancer is one of the leading causes of death worldwide. It is considered that genetic factors and epigenetic changes allow cells to proliferate in an uncontrolled manner by escaping essential regulatory mechanisms. Rigorous cancer research in the past few decades supported by advances in cell and molecular biology has led scientists to clearly understand there are genetic changes associated with cancer incidences that cause the disease to grow and spread to other parts of the body. Cancer is initiated as the result of uncontrolled cell division and proliferation leading to tumor formation which culminates in metastasis that involves the dissemination of tumor cells to new sites in the body forming secondary tumors, and is responsible for about 90% of cancer-related deaths in reality. Cell proliferation requires a balanced rate of cell growth and division to maintain the increase in cell numbers for growth and development, maintenance of tissue homeostasis and wound healing. Cancer progression is frequently associated with increased cell proliferation, metabolic dysregulation, resistance to apoptosis, genetic instability, initiation of angiogenesis, invasion and increased migration of cells. Genetic changes appearing in the information system of cells that program its unregulated growth and proliferation gradually lead to the manifestation of cancer and therapeutic options must be directed accordingly [1]. The critical roles played by some of the molecules associated with specific oncogenic pathways and the cellular microenvironment that lead to cancer progression and metastasis have been precisely described in recent years based on findings from the Human Genome Project. New developments in DNA and RNA analysis have made it possible to study underlying genetic changes systematically. These advances have allowed researchers to have a more in-depth understanding of the signaling pathways and processes involved, in carcinogenesis and have led to the identification of critical pathways that can be successfully targeted for therapeutic purposes [2]. Importantly, epidemiological studies have consistently shown that environmental factors or lifestyle changes involving mutagenic agents are the primary culprits. Thus, it is not only necessary to associate genetic mutations with different cancers but also to work on the mechanism of action of mutagens by focusing on enzymes which could invariably mediate oncogenic transformations. For example, overexpression of the ribonucleotide reductase (RnR) enzyme which catalyzes the formation of deoxyribonucleotides from ribonucleotides necessary for cell division, is implicated in many forms of cancer and the genes for the components of the enzyme are often mutated, leading to hyperactivity of the enzyme. But there are instances indicating that cytoplasmic material rather than the karyoplast would be responsible for cellular transformation that might be better explained as a consequence of certain epigenetic modulation than purely genetic changes. RnR active site inhibitors have been developed to biophysically deactivate the enzyme when necessary, with positive results [3].

Over the years, technological advances in the field of molecular biology have been exploited to unravel genetic and epigenetic changes to fully understand the pathogenesis of human cancer. The range of cancer-causing mutations is known to be huge, and the mutational landscape differs from one another depending on the type of cancer and even people suffering from the same cancer type are found to have considerably different mutation patterns. Moreover, it has long been observed that every patient responds differently to particular treatments despite having the same type and stage of cancer. These observations have been compelling and led researchers to adopt a precision medicine approach to cancer therapy necessitating the study of genetic features of vulnerable individuals for a patient-specific treatment regimen towards the most effective treatment of cancer. Precision oncology has evolved as a form of cancer therapy focused on genetic profiling of tumors to identify molecular alterations involved in cancer development for tailored individualized treatment of the disease [4,5]. The emergence of next-generation sequencing (NGS) in 2005 has proved to be massively important in this direction as the technology is used to determine the order of nucleotides in entire genomes or targeted regions of DNA or RNA and has revolutionized biological research, allowing scientists to study biological systems at a level never tried before. It can provide new insights into the nature of genes and proteins thought to be associated with cancer, and the application of evolving molecular techniques to the study of cancer has also provided markers that have led to new advances in tumor diagnosis, prognosis, and treatment which have proven to be immensely helpful in advancing precision oncology [6].

Cancer development generally is a multi-step process triggered by mutations leading to the activation of specific oncogenic pathways with the concurrent inactivation of tumor suppressor genes that act as sentinels to control unwanted cell growth, proliferation, tumor microenvironment (TME) remodeling, epithelial to
mesenchymal transition (EMT), etc. Scientists have been trying to analyze the totality of cancer-causing gene mutations regarded as the “mutational landscape”, of different types of cancer types and to target them effectively for cancer cure [7,8]. Most of these biochemical processes are conserved in model organisms such as the free-living transparent nematode *Caenorhabditis elegans* and the fruit fly *Drosophila melanogaster* alongside mice and other large animal models, and are widely used due to the ease of their genetic manipulation to study the complex biology of cancer. The somatic cell mutations, called somatic structural variants (SVs), have been shown to account for more than half of all cancer-causing mutations. These are the variants or mutations different from the hereditary or germline variants that have passed from parents to offspring and become incorporated into the DNA of every cell in the body [9]. The somatic SVs can be noticed in the transformed cells and in their daughter cells that may continue to grow because of errors in DNA copying and their repair mechanisms during cell division thereby altering the genomic structure which will become more numerous with time. Although somatic SVs play a crucial role in cancer development, relatively little has been known about their mode of action in cancer development. Methods to detect and identify the functional effects of these SVs are sure to enable researchers to understand the molecular consequences of individual somatic mutations in cancer. The findings related to the mutation-specific alterations could be used to develop therapies that target the mutated cells, opening new possibilities in cancer therapy. Furthermore, most of the human genome consists of noncoding regions, and studies on variations in the noncoding regions of the cancer cells reveal additional mechanisms underlying cancer progression. For example, changes in noncoding regions such as point mutations and complex genomic rearrangements can disrupt or create transcription factor-binding sites or even affect non-coding RNA loci leaving options for unwanted changes in the gene expression pattern of the cell. Cancer whole-genome sequencing (WGS) remains the most comprehensive method for identifying variants in non-coding regions as targeted approaches like exome sequencing (WES) may miss certain variants residing outside the coding regions. Pieces of evidence suggest oncogenesis typically involves interplay between germline and somatic variants and different modes of action of non-coding variants could further potentiate these developments. Thus, a systematic approach to unraveling the roles of the non-coding genome in cancer progression should help improve cancer diagnosis and therapy [10].

## 2. Initiatives to identify tumor cell reprogramming and targeted cancer therapy

The landmark Cancer Genomics Program launched in 2006 has contributed immensely to the awareness of the importance of cancer genomics in our understanding of cancer over the past decade and has begun to change the way the disease is treated in clinic. A large number of mutations contribute to cancer and predicting the effects of mutations using in silico tools has become a frequently used approach, but the use of next-generation sequencing-based approaches in clinical diagnosis has also led to a considerable increase in data and a vast number of variants of uncertain significance that require further analysis and validation to achieve the development goals. These data cannot be analyzed simply by using the tools and techniques traditionally available to better understand the origin and evolution of cancer and therefore to achieve this goal, a cancer reference framework through modeling of genome sequencing data has been proposed for the systematic identification of representative driver networks to predict cancer progression and associated clinical phenotypes. It is based on the consideration that possible observable combinations of these mutations must converge on a few common signaling pathways and networks responsible for tumor growth and cancer progression. In this way, it aims to analyze data to explain how different genetic mutations in different patients have the same downstream effects on the protein machinery, ultimately leading to the analysis of the characteristic pathway of cancer progression. In this regard, The Cancer Genome Atlas Program (TCGA) is the landmark cancer genomics program initiated by the NIH, and has contributed immensely to realizing the importance of genomics in cancer research [11,12]. It has molecularly characterized over 20,000 primary cancer and successfully matched normal samples spanning 33 cancer types. The synchronized vision of oncogenic processes based on PanCancer Atlas analyzes attempts to elucidate the possible consequences of genome alterations on the different signaling pathways involved in human cancers, also reflecting on their influence on the tumor microenvironment and immune cells, to provide new information about development of new forms of targeted drugs and immunotherapies. Considering the genes and
mesenchymal transition (EMT), etc. Scientists have been trying to analyze the totality of cancer-causing gene mutations regarded as the “mutational landscape”, of different types of cancer types and to target them effectively for cancer cure [7,8]. Most of these biochemical processes are conserved in model organisms such as the free-living transparent nematode *Caenorhabditis elegans* and the fruit fly *Drosophila melanogaster* alongside mice and other large animal models, and are widely used due to the ease of their genetic manipulation to study the complex biology of cancer. The somatic cell mutations, called somatic structural variants (SVs), have been shown to account for more than half of all cancer-causing mutations. These are the variants or mutations different from the hereditary or germline variants that have passed from parents to offspring and become incorporated into the DNA of every cell in the body [9]. The somatic SVs can be noticed in the transformed cells and in their daughter cells that may continue to grow because of errors in DNA copying and their repair mechanisms during cell division thereby altering the genomic structure which will become more numerous with time. Although somatic SVs play a crucial role in cancer development, relatively little has been known about their mode of action in cancer development. Methods to detect and identify the functional effects of these SVs are sure to enable researchers to understand the molecular consequences of individual somatic mutations in cancer. The findings related to the mutation-specific alterations could be used to develop therapies that target the mutated cells, opening new possibilities in cancer therapy. Furthermore, most of the human genome consists of noncoding regions, and studies on variations in the noncoding regions of the cancer cells reveal additional mechanisms underlying cancer progression. For example, changes in noncoding regions such as point mutations and complex genomic rearrangements can disrupt or create transcription factor-binding sites or even affect non-coding RNA loci leaving options for unwanted changes in the gene expression pattern of the cell. Cancer whole-genome sequencing (WGS) remains the most comprehensive method for identifying variants in non-coding regions as targeted approaches like exome sequencing (WES) may miss certain variants residing outside the coding regions. Pieces of evidence suggest oncogenesis typically involves interplay between germline and somatic variants and different modes of action of non-coding variants could further potentiate these developments. Thus, a systematic approach to unraveling the roles of the non-coding genome in cancer progression should help improve cancer diagnosis and therapy [10].

## 2. Initiatives to identify tumor cell reprogramming and targeted cancer therapy

The landmark Cancer Genomics Program launched in 2006 has contributed immensely to the awareness of the importance of cancer genomics in our understanding of cancer over the past decade and has begun to change the way the disease is treated in clinic. A large number of mutations contribute to cancer and predicting the effects of mutations using in silico tools has become a frequently used approach, but the use of next-generation sequencing-based approaches in clinical diagnosis has also led to a considerable increase in data and a vast number of variants of uncertain significance that require further analysis and validation to achieve the development goals. These data cannot be analyzed simply by using the tools and techniques traditionally available to better understand the origin and evolution of cancer and therefore to achieve this goal, a cancer reference framework through modeling of genome sequencing data has been proposed for the systematic identification of representative driver networks to predict cancer progression and associated clinical phenotypes. It is based on the consideration that possible observable combinations of these mutations must converge on a few common signaling pathways and networks responsible for tumor growth and cancer progression. In this way, it aims to analyze data to explain how different genetic mutations in different patients have the same downstream effects on the protein machinery, ultimately leading to the analysis of the characteristic pathway of cancer progression. In this regard, The Cancer Genome Atlas Program (TCGA) is the landmark cancer genomics program initiated by the NIH, and has contributed immensely to realizing the importance of genomics in cancer research [11,12]. It has molecularly characterized over 20,000 primary cancer and successfully matched normal samples spanning 33 cancer types. The synchronized vision of oncogenic processes based on PanCancer Atlas analyzes attempts to elucidate the possible consequences of genome alterations on the different signaling pathways involved in human cancers, also reflecting on their influence on the tumor microenvironment and immune cells, to provide new information about development of new forms of targeted drugs and immunotherapies. Considering the genes and
pathways affecting different cancer types and individual tumors vary considerably, a complete understanding of these alterations becomes essential to identify vulnerabilities and discover precise therapeutic solutions. A comprehensive analysis of tumors based on their genomic studies must reveal the alterations in signaling pathways indicating patterns of vulnerabilities and the means to identify prospective targets for the development of personalized treatments and new combination therapies. The TCGA Research Network has profiled and analyzed a large number of human tumors to discover molecular aberrations at the DNA, RNA, protein, and epigenetic levels and thereby provided reliable diagnostic and prognostic biomarkers for different cancer types since then [13,14].

Further, the Cancer Cell Map Initiative (CCMI), launched in 2015 by researchers at the University of California, San Francisco and the University of California, San Diego, allowed researchers to determine how hundreds of genetic mutations involved in a few types of cancer affect the activity of certain crucial proteins which ultimately lead to the manifestation of cancer [15]. Although the presence of mutated genes is strongly correlated with cancer incidence, very specific causative genes or a small set of genes for most cancers have not been confirmed after decades of genomic studies. Nobel laureate James D. Watson spoke at Cancer World 2013: "We can go ahead and sequence every piece of DNA that has ever existed, but I don't think we'll find the Achilles heel of cancer. In this direction, TCGA network has provided a large amount of data to analyze to clarify how the disease begins and progresses. The mission of CCMI is to enable a new era of cancer discovery and treatment based on the complete elucidation of the molecular networks underlying cancer. As there is a large amount of sequence data from many different cancer types, efforts are being made to extract mechanistic insights from the available information, requiring an integrated computational and experimental strategy that will help place these alterations in the higher order contexts of signaling mechanisms in cancer cells. This is the defined goal of the CCMI and has the potential to create a resource that can be used for cancer genome interpretation, enabling the identification of key complexes and pathways to be studied more mechanistically to better understand the biology underlying different cancer types and conditions [16].

Additionally, the Cancer Dependency Map (DepMap) initiative at the Broad Institute of MIT and Harvard, an academic-industry partnership program officially announced in 2019, is devoted to cancer research aimed at accelerating precision cancer medicine by creating a comprehensive map of tumor vulnerabilities and identifying key cancer biomarkers. This program focuses on screening thousands of cancer cell lines using RNA interference (RNAi) and CRISPR-Cas9 gene editing strategies to identify genes whose expression may be affected and found to be essential for cell transformation. CRISPR-Cas9 gene editing is an efficient method of modifying the genome of almost any cell type. CRISPR editing and screening have emerged as powerful tools for studying nearly all aspects of cellular behaviors which have greatly influenced our understanding of cancer biology and continue to contribute to new discoveries [17,18]. A related project called Cancer Cell Line Encyclopedia (CCLE), started as a collaboration between the Broad Institute and the Novartis Institute for Biomedical Research in 2008, appears well suited for large-scale genetic characterization of thousands of cancer cell lines in order to link characteristics genetic alterations with distinct pharmacological vulnerabilities, and to translate integrative genomics into patients stratification for personalized cancer treatments. By accessing critical genomic data via CCLE, such as gene mutations, chromosome copy number, gene expression and methylation profiles, scientists can now predict new synthetic lethality and identify new molecular markers for selectively targeting cells with specific genetic changes. Thus, the initiative provides a rigorous foundation on which to study genetic variants and candidate targets, identify new marker-based cancer diagnostics, and design anticancer agents for critical cancers therapies p[19,20]. The challenge of identifying relevant genes and signaling molecules for different types of cancer using cutting-edge technologies will remain an essential part of cancer research and precision oncology and will most likely help vulnerable individuals receive effective treatment for cancer.

### 3. Single-cell Technology Reveals Tumor Heterogeneity Critical to Cancer Therapy

Tumor heterogeneity is a hallmark property of cancer development and broadly refers to the differences between tumors of the same type in different patients, the differences between a primary and a secondary tumor, and the differences in genomic and phenotypic profiles displayed by cells within a single tumor. Heterogeneity
pathways affecting different cancer types and individual tumors vary considerably, a complete understanding of these alterations becomes essential to identify vulnerabilities and discover precise therapeutic solutions. A comprehensive analysis of tumors based on their genomic studies must reveal the alterations in signaling pathways indicating patterns of vulnerabilities and the means to identify prospective targets for the development of personalized treatments and new combination therapies. The TCGA Research Network has profiled and analyzed a large number of human tumors to discover molecular aberrations at the DNA, RNA, protein, and epigenetic levels and thereby provided reliable diagnostic and prognostic biomarkers for different cancer types since then [13,14].

Further, the Cancer Cell Map Initiative (CCMI), launched in 2015 by researchers at the University of California, San Francisco and the University of California, San Diego, allowed researchers to determine how hundreds of genetic mutations involved in a few types of cancer affect the activity of certain crucial proteins which ultimately lead to the manifestation of cancer [15]. Although the presence of mutated genes is strongly correlated with cancer incidence, very specific causative genes or a small set of genes for most cancers have not been confirmed after decades of genomic studies. Nobel laureate James D. Watson spoke at Cancer World 2013: "We can go ahead and sequence every piece of DNA that has ever existed, but I don't think we'll find the Achilles heel of cancer. In this direction, TCGA network has provided a large amount of data to analyze to clarify how the disease begins and progresses. The mission of CCMI is to enable a new era of cancer discovery and treatment based on the complete elucidation of the molecular networks underlying cancer. As there is a large amount of sequence data from many different cancer types, efforts are being made to extract mechanistic insights from the available information, requiring an integrated computational and experimental strategy that will help place these alterations in the higher order contexts of signaling mechanisms in cancer cells. This is the defined goal of the CCMI and has the potential to create a resource that can be used for cancer genome interpretation, enabling the identification of key complexes and pathways to be studied more mechanistically to better understand the biology underlying different cancer types and conditions [16].

Additionally, the Cancer Dependency Map (DepMap) initiative at the Broad Institute of MIT and Harvard, an academic-industry partnership program officially announced in 2019, is devoted to cancer research aimed at accelerating precision cancer medicine by creating a comprehensive map of tumor vulnerabilities and identifying key cancer biomarkers. This program focuses on screening thousands of cancer cell lines using RNA interference (RNAi) and CRISPR-Cas9 gene editing strategies to identify genes whose expression may be affected and found to be essential for cell transformation. CRISPR-Cas9 gene editing is an efficient method of modifying the genome of almost any cell type. CRISPR editing and screening have emerged as powerful tools for studying nearly all aspects of cellular behaviors which have greatly influenced our understanding of cancer biology and continue to contribute to new discoveries [17,18]. A related project called Cancer Cell Line Encyclopedia (CCLE), started as a collaboration between the Broad Institute and the Novartis Institute for Biomedical Research in 2008, appears well suited for large-scale genetic characterization of thousands of cancer cell lines in order to link characteristics genetic alterations with distinct pharmacological vulnerabilities, and to translate integrative genomics into patients stratification for personalized cancer treatments. By accessing critical genomic data via CCLE, such as gene mutations, chromosome copy number, gene expression and methylation profiles, scientists can now predict new synthetic lethality and identify new molecular markers for selectively targeting cells with specific genetic changes. Thus, the initiative provides a rigorous foundation on which to study genetic variants and candidate targets, identify new marker-based cancer diagnostics, and design anticancer agents for critical cancers therapies p[19,20]. The challenge of identifying relevant genes and signaling molecules for different types of cancer using cutting-edge technologies will remain an essential part of cancer research and precision oncology and will most likely help vulnerable individuals receive effective treatment for cancer.

### 3. Single-cell Technology Reveals Tumor Heterogeneity Critical to Cancer Therapy

Tumor heterogeneity is a hallmark property of cancer development and broadly refers to the differences between tumors of the same type in different patients, the differences between a primary and a secondary tumor, and the differences in genomic and phenotypic profiles displayed by cells within a single tumor. Heterogeneity
within a single tumor, referred to as genetic intratumoral heterogeneity (ITH), has been documented across most
cancers as an outcome of genome instability and clonal evolution [21,22]. Tumor heterogeneity appears to be a
critical phenomenon in the history of individual cancers, as its translational significance may reflect on tumor
progression, disease recurrence, treatment response, and resistance [23]. Recent investigations on drug resistance
and tumor heterogeneity have confirmed the clonal organization of tumors as the underlying basis for drug
resistance, thus indicating the need to fully understand the structure and dynamics of ITH to develop advanced
treatment strategies for cancer [24,25]. More precisely the cellular composition of a tumor is known, the
underlying mechanism of disease progression is understood, and/or molecules and pathways involved in the
process are identified, and more specific therapeutic strategies could be devised to get the desired result. It is the
stated goal of precision oncology and the emergence of single-cell technologies for biological analysis has
become the crucial tool in this regard as they can carry out accurate single-cell measurements to provide a clear
picture of tumor heterogeneity and reveal how structural changes in chromosomes can lead to the complex
biological processes involved with carcinogenesis [26,27]. The rapid progress in the development of NGS in
recent years has provided many valuable insights into cancer genomics, and NGS-based technologies for
genomics, transcriptomics, and epigenomics have enabled laboratories to carry out related single-cell
measurements efficiently. Single-cell genomics now facilitates the simultaneous measurement of thousands of
genes in thousands of ‘single’ cells from a single specimen, allowing researchers to compare genomes of
individual cells to determine the mutational profile of the affected cells to better understand the molecular
consequences of different variants present in the tumor. The single-cell template strand sequencing
(Strand-seq), a special single-cell sequencing technology now enables independent and efficient analysis of the
twoparental DNA strands resolving homologous chromosomes similar in shape and structure but not identical
within single cells which is crucial to identifying somatic SVs, understanding genomic rearrangements
and unmask tissue heterogeneity. Moreover, single-cell sequencing can also be combined with CRISPR knockout
screening that exploits the efficiency and flexibility of CRISPR-Cas9 genome editing to enable large-scale studies
regarding how genetic modification can affect cell behavior or gain insights into a specific physiological
condition required to fully understand the underlying cellular events [28].

Combining the CRISPR-Cas system with single-cell techniques for studying gene functions with the
concurrent use of single-cell resolution techniques, such as flow cytometry, microfluidics, manual cell picking, or
micromanipulation, can be exploited in cancer research in many ways, including identifying novel drug targets,
studying unknown mechanisms of action of drugs and designing treatment regimen [29]. The importance of
epigenetic reprogramming in cancer is well understood, as evidenced by the fact that chromatin regulators are
often mutated in the affected cells and the widespread epigenetic, changes throughout cancer genomes can be
identified and linked to the activities of different known oncogenes and tumor suppressor genes. Abnormal
epigenetic changes are usually influenced by aging, viruses, and dietary and environmental factors that frequently
contribute to cancer development. The interrelationship between genetic and epigenetic changes needs to be
further examined for the discovery of screening markers to optimize pathways of diagnosis and prognosis and to
develop strategies for individualized cancer treatment [30]. For example, DNA methylation is known to be
associated with cell differentiation, aging, and diseases including cancer. A considerable amount of understanding
exists regarding tissue- specific DNA methylation patterns, but it would reveal much less information about
person- specific DNA methylation causing cancer. Thus, the premise of single-cell epigenome profiling holds
great possibilities for deciphering the cellular states and characterizing tumor heterogeneity with an option for
therapeutic interventions to pin specific mutations having profound effects on epigenetic pathways. The inclusion
of epigenetics in clinical practice would require identifying epigenetic signatures that mediate distinct
phenotypical changes of clinical relevance, such as mesenchymal transition, stems, dormancy, and quiescence or
therapy resistance.

Single-cell sequencing technologies have largely been successful in leading scientists to understand the cell
types and features associated with the tumor yet, the spatial context of this development is essential to better
understand how cells organize and communicate across the tissue to fully unlock the repertoire of tumor
heterogeneity. It requires a clear understanding of which cells are present, where they are situated in tissue, their
biomarker expression patterns, and how they organize and interact to influence the tissue microenvironment. This
is an essential part of spatial biology and adds another dimension to single-cell analysis to unmask tumor
within a single tumor, referred to as genetic intratumoral heterogeneity (ITH), has been documented across most
cancers as an outcome of genome instability and clonal evolution [21,22]. Tumor heterogeneity appears to be a
critical phenomenon in the history of individual cancers, as its translational significance may reflect on tumor
progression, disease recurrence, treatment response, and resistance [23]. Recent investigations on drug resistance
and tumor heterogeneity have confirmed the clonal organization of tumors as the underlying basis for drug
resistance, thus indicating the need to fully understand the structure and dynamics of ITH to develop advanced
treatment strategies for cancer [24,25]. More precisely the cellular composition of a tumor is known, the
underlying mechanism of disease progression is understood, and/or molecules and pathways involved in the
process are identified, and more specific therapeutic strategies could be devised to get the desired result. It is the
stated goal of precision oncology and the emergence of single-cell technologies for biological analysis has
become the crucial tool in this regard as they can carry out accurate single-cell measurements to provide a clear
picture of tumor heterogeneity and reveal how structural changes in chromosomes can lead to the complex
biological processes involved with carcinogenesis [26,27]. The rapid progress in the development of NGS in
recent years has provided many valuable insights into cancer genomics, and NGS-based technologies for
genomics, transcriptomics, and epigenomics have enabled laboratories to carry out related single-cell
measurements efficiently. Single-cell genomics now facilitates the simultaneous measurement of thousands of
genes in thousands of ‘single’ cells from a single specimen, allowing researchers to compare genomes of
individual cells to determine the mutational profile of the affected cells to better understand the molecular
consequences of different variants present in the tumor. The single-cell template strand sequencing
(Strand-seq), a special single-cell sequencing technology now enables independent and efficient analysis of the
twoparental DNA strands resolving homologous chromosomes similar in shape and structure but not identical
within single cells which is crucial to identifying somatic SVs, understanding genomic rearrangements
and unmask tissue heterogeneity. Moreover, single-cell sequencing can also be combined with CRISPR knockout
screening that exploits the efficiency and flexibility of CRISPR–Cas9 genome editing to enable large-scale studies
regarding how genetic modification can affect cell behavior or gain insights into a specific physiological
condition required to fully understand the underlying cellular events [28].

Combining the CRISPR-Cas system with single-cell techniques for studying gene functions with the
concurrent use of single-cell resolution techniques, such as flow cytometry, microfluidics, manual cell picking, or
micromanipulation, can be exploited in cancer research in many ways, including identifying novel drug targets,
studying unknown mechanisms of action of drugs and designing treatment regimen [29]. The importance of
epigenetic reprogramming in cancer is well understood, as evidenced by the fact that chromatin regulators are
often mutated in the affected cells and the widespread epigenetic, changes throughout cancer genomes can be
identified and linked to the activities of different known oncogenes and tumor suppressor genes. Abnormal
epigenetic changes are usually influenced by aging, viruses, and dietary and environmental factors that frequently
contribute to cancer development. The interrelationship between genetic and epigenetic changes needs to be
further examined for the discovery of screening markers to optimize pathways of diagnosis and prognosis and to
develop strategies for individualized cancer treatment [30]. For example, DNA methylation is known to be
associated with cell differentiation, aging, and diseases including cancer. A considerable amount of understanding
exists regarding tissue- specific DNA methylation patterns, but it would reveal much less information about
person- specific DNA methylation causing cancer. Thus, the premise of single-cell epigenome profiling holds
great possibilities for deciphering the cellular states and characterizing tumor heterogeneity with an option for
therapeutic interventions to pin specific mutations having profound effects on epigenetic pathways. The inclusion
of epigenetics in clinical practice would require identifying epigenetic signatures that mediate distinct
phenotypical changes of clinical relevance, such as mesenchymal transition, stems, dormancy, and quiescence or
therapy resistance.

Single-cell sequencing technologies have largely been successful in leading scientists to understand the cell
types and features associated with the tumor yet, the spatial context of this development is essential to better
understand how cells organize and communicate across the tissue to fully unlock the repertoire of tumor
heterogeneity. It requires a clear understanding of which cells are present, where they are situated in tissue, their
biomarker expression patterns, and how they organize and interact to influence the tissue microenvironment. This
is an essential part of spatial biology and adds another dimension to single-cell analysis to unmask tumor
heterogeneity [31,32]. Spatial biology simply tries to combine whole-slide imaging (WSI), commonly referred to as 'virtual microscopy', at single-cell resolution to visualize and quantitate biomarker expression and reveal how cells interact and organize across the entire tissue landscape. This technique can support research for early biomarker discovery to late-stage translational research and therapy development. The latest development in this direction is spatial transcriptomics which has enabled researchers to visualize and quantify RNA down to the subcellular level and simultaneously compare gene expression in situ. It is a groundbreaking molecular profiling method that exploits multi-omics technologies allowing researchers to measure all the gene activity in a tissue sample and assay the genetic information of single cells within their native tissue environment [33,34]. The growing ability to demonstrate the role and function of distinct cell types present in the tissue has paved the way for a new understanding of the tissue-specific cellular pathways and interactions that lead to cancer manifestation. Thus, molecular analysis of cancer cells based on single-cell technologies aims to present an accurate picture of the most recent developments regarding changes in genes and proteins responsible for alterations in cellular processes, enabling a better understanding of prognosis and pathways of development of cancer. New advances in multi-omics techniques powered by AI h now enable researchers to integrate genomic, transcriptomic, epigenomic, and other related data to gain the most accurate information on the activity state of individual genes and proteins to reveal the novel cancer drivers and genetic vulnerabilities for prevention and cure [35,36]. The emerging field of single-cell technology thus provides an unprecedented insight into the complex genetic and epigenetic heterogeneity within individual tumors for advanced precision oncology-based treatment and is likely to streamline future research directions [37,38].

## 4. Signaling Pathway Deregulation and Targeted Drug Therapy of Cancer

The root cause underlying cancer progression is genetic and epigenetic alterations in the affected cells leading them to grow and proliferate uncontrollably, although the progression of cancer remains dependent on a complex interplay between the tumor cells and surrounding non-neoplastic stromal cells and ECM present in the tumor microenvironment [39,40]. Cell signaling network as the foremost system of communication between cells and the surroundings that involve a variety of chemical and mechanical signals to regulate different signaling pathways comes into consideration here as all the essentials of cellular behaviors like cell growth and proliferation, cell polarity, cell metabolism, differentiation, survival, and migration can be seen guided by the components of these pathways working in a collaborative manner in the cell. The signaling pathways together maintain an internal circuitry inside cells guided by external stimuli enabling them to sense whether their state of attachment to ECM and other cells is appropriate and if different growth factors, hormones, and cytokines guide them to proliferate or differentiate, move, or stay put for now, or to commit to cell death by apoptosis or autophagy. Almost all gene modifications can be related to one or more of these signaling pathways that are deregulated in the affected cells to acquire hallmark properties of cancer [41]. Cancer cell signaling displays altered expressions of the componentsof the signaling network that include many secreted protein receptors, growth factors, protein kinases, phosphatases, different cytoplasmic proteins, and transcription factors leading individual cells to respond to the changes with appropriate physiological behaviors. Cell division is mainly regulated by a group of extracellular growth factors that signal resting cells to divide by exploiting the intrinsic regulatory process of the cell. Cytokines ordinarily signal the immune cells to mount coordinated attacks on invading bacteria, and viruses and play essential roles in cancer prevention. Thus, signals propagated by growth factors and cytokines can simply tell individual cells to divide or not under particular conditions whose alterations could lead to the pathophysiology of cancer. The earliest information regarding the relationship between cancer and growth factors came from the observation that normal cells in culture often required serum for proliferation, while cancer cells had a much less requirement for serum. The serum is known for providing growth factors among other ingredients needed for the overall regulation of the cell cycle. The other hints came from gene mutations found in cancer cells observed to cause changes in cell behaviors very similar to those related to the activities of growth factors and their receptors. The oncogenic mutations disrupt the cellular circuits that control cell adhesion and signaling, enabling cells that carry them to over-proliferate and invade the other tissues in an uncontrolled fashion. Many of these mutations have been directly linked to the growth factors and their receptor
heterogeneity [31,32]. Spatial biology simply tries to combine whole-slide imaging (WSI), commonly referred to as 'virtual microscopy', at single-cell resolution to visualize and quantitate biomarker expression and reveal how cells interact and organize across the entire tissue landscape. This technique can support research for early biomarker discovery to late-stage translational research and therapy development. The latest development in this direction is spatial transcriptomics which has enabled researchers to visualize and quantify RNA down to the subcellular level and simultaneously compare gene expression in situ. It is a groundbreaking molecular profiling method that exploits multi-omics technologies allowing researchers to measure all the gene activity in a tissue sample and assay the genetic information of single cells within their native tissue environment [33,34]. The growing ability to demonstrate the role and function of distinct cell types present in the tissue has paved the way for a new understanding of the tissue-specific cellular pathways and interactions that lead to cancer manifestation. Thus, molecular analysis of cancer cells based on single-cell technologies aims to present an accurate picture of the most recent developments regarding changes in genes and proteins responsible for alterations in cellular processes, enabling a better understanding of prognosis and pathways of development of cancer. New advances in multi-omics techniques powered by AI h now enable researchers to integrate genomic, transcriptomic, epigenomic, and other related data to gain the most accurate information on the activity state of individual genes and proteins to reveal the novel cancer drivers and genetic vulnerabilities for prevention and cure [35,36]. The emerging field of single-cell technology thus provides an unprecedented insight into the complex genetic and epigenetic heterogeneity within individual tumors for advanced precision oncology-based treatment and is likely to streamline future research directions [37,38].

## 4. Signaling Pathway Deregulation and Targeted Drug Therapy of Cancer

The root cause underlying cancer progression is genetic and epigenetic alterations in the affected cells leading them to grow and proliferate uncontrollably, although the progression of cancer remains dependent on a complex interplay between the tumor cells and surrounding non-neoplastic stromal cells and ECM present in the tumor microenvironment [39,40]. Cell signaling network as the foremost system of communication between cells and the surroundings that involve a variety of chemical and mechanical signals to regulate different signaling pathways comes into consideration here as all the essentials of cellular behaviors like cell growth and proliferation, cell polarity, cell metabolism, differentiation, survival, and migration can be seen guided by the components of these pathways working in a collaborative manner in the cell. The signaling pathways together maintain an internal circuitry inside cells guided by external stimuli enabling them to sense whether their state of attachment to ECM and other cells is appropriate and if different growth factors, hormones, and cytokines guide them to proliferate or differentiate, move, or stay put for now, or to commit to cell death by apoptosis or autophagy. Almost all gene modifications can be related to one or more of these signaling pathways that are deregulated in the affected cells to acquire hallmark properties of cancer [41]. Cancer cell signaling displays altered expressions of the componentsof the signaling network that include many secreted protein receptors, growth factors, protein kinases, phosphatases, different cytoplasmic proteins, and transcription factors leading individual cells to respond to the changes with appropriate physiological behaviors. Cell division is mainly regulated by a group of extracellular growth factors that signal resting cells to divide by exploiting the intrinsic regulatory process of the cell. Cytokines ordinarily signal the immune cells to mount coordinated attacks on invading bacteria, and viruses and play essential roles in cancer prevention. Thus, signals propagated by growth factors and cytokines can simply tell individual cells to divide or not under particular conditions whose alterations could lead to the pathophysiology of cancer. The earliest information regarding the relationship between cancer and growth factors came from the observation that normal cells in culture often required serum for proliferation, while cancer cells had a much less requirement for serum. The serum is known for providing growth factors among other ingredients needed for the overall regulation of the cell cycle. The other hints came from gene mutations found in cancer cells observed to cause changes in cell behaviors very similar to those related to the activities of growth factors and their receptors. The oncogenic mutations disrupt the cellular circuits that control cell adhesion and signaling, enabling cells that carry them to over-proliferate and invade the other tissues in an uncontrolled fashion. Many of these mutations have been directly linked to the growth factors and their receptor
proteins involved with tumor growth, angiogenesis, invasion, and metastases [42,43].

A critically important finding of cell signaling is that one kind of cell membrane receptor can mediate many different downstream intracellular pathways and one pathway can also be activated by several of the upstream surface receptors revealing common signaling components in multiple signaling pathways. For example, the RTKs, like EGFR, FGFR, IGFR, VEGFR, PDGFR, and the GPCRs, can all activate the MAPK cascade while the widely studied RTKs such as EGFR/HER family receptor can initiate different signaling pathways including mitogen- activated protein kinase (MAPK), phosphoinositide-3-kinase (PI3K)/AKT, and mammalian target of rapamycin (mTOR) pathways involved in regulations of cell growth, proliferation, differentiation, and survival. This feature of the signaling process evidently presents the option for crosstalk between components of different signaling pathways at different stages of the cellular process. A molecule participating in crosstalk can affect the activation of alternate signaling pathways, and receptors can also have an altered ability to bind to the ligands which can swiftly lead to cancer manifestation. As generally observed, most of the cell signaling pathways contribute to the development of cancer and seldom does a cancer type arise from the deregulation of a single pathway. Breast cancer can arise due to elevated expression of the estrogen receptor (ER), EGFR/HER, or IGFR, but in many cases, molecules and intermediates of multiple signaling pathways can be interactively involved in the process. In this way, the many signaling molecules affecting cancer cells together could be reconsidered to create elaborate integrated circuits within the cell, derived from the usual signaling circuits that operate in normal cells. The transformed intracellular circuit could be divided into distinct subcircuits specialized in specific cellular activities to promote hallmark features of cancer [44] (Fig. 1). Signal transduction leading to tumor growth, cancer cell migration, metastasis, and drug resistance are often complex processes, as cancer cells typically develop abnormalities in multiple signaling pathways or rely on crosstalk between different pathways and some redundant pathways for maintenance of growth and survival.

<figure><img src="image_2.png" /><figcaption>**Figure 1.** Intracellular Signaling Networks Regulate the Operations of the Cancer Cell.
An elaborate integrated circuit operates within normal cells and is reprogrammed to regulate hallmark capabilities within cancer cells. Separate sub-circuits, depicted here in differently colored fields, are specialized to orchestrate the various capabilities. At one level, this depiction is simplistic, as there is considerable crosstalk between such sub-circuits. In addition, because each cancer cell is exposed to a complex mixture of signals from its</figcaption></figure>
proteins involved with tumor growth, angiogenesis, invasion, and metastases [42,43].

A critically important finding of cell signaling is that one kind of cell membrane receptor can mediate many different downstream intracellular pathways and one pathway can also be activated by several of the upstream surface receptors revealing common signaling components in multiple signaling pathways. For example, the RTKs, like EGFR, FGFR, IGFR, VEGFR, PDGFR, and the GPCRs, can all activate the MAPK cascade while the widely studied RTKs such as EGFR/HER family receptor can initiate different signaling pathways including mitogen- activated protein kinase (MAPK), phosphoinositide-3-kinase (PI3K)/AKT, and mammalian target of rapamycin (mTOR) pathways involved in regulations of cell growth, proliferation, differentiation, and survival. This feature of the signaling process evidently presents the option for crosstalk between components of different signaling pathways at different stages of the cellular process. A molecule participating in crosstalk can affect the activation of alternate signaling pathways, and receptors can also have an altered ability to bind to the ligands which can swiftly lead to cancer manifestation. As generally observed, most of the cell signaling pathways contribute to the development of cancer and seldom does a cancer type arise from the deregulation of a single pathway. Breast cancer can arise due to elevated expression of the estrogen receptor (ER), EGFR/HER, or IGFR, but in many cases, molecules and intermediates of multiple signaling pathways can be interactively involved in the process. In this way, the many signaling molecules affecting cancer cells together could be reconsidered to create elaborate integrated circuits within the cell, derived from the usual signaling circuits that operate in normal cells. The transformed intracellular circuit could be divided into distinct subcircuits specialized in specific cellular activities to promote hallmark features of cancer [44] (Fig. 1). Signal transduction leading to tumor growth, cancer cell migration, metastasis, and drug resistance are often complex processes, as cancer cells typically develop abnormalities in multiple signaling pathways or rely on crosstalk between different pathways and some redundant pathways for maintenance of growth and survival.

<figure><img src="image_2.png" /><figcaption>**Figure 1.** Intracellular Signaling Networks Regulate the Operations of the Cancer Cell.
An elaborate integrated circuit operates within normal cells and is reprogrammed to regulate hallmark capabilities within cancer cells. Separate sub-circuits, depicted here in differently colored fields, are specialized to orchestrate the various capabilities. At one level, this depiction is simplistic, as there is considerable crosstalk between such sub-circuits. In addition, because each cancer cell is exposed to a complex mixture of signals from its</figcaption></figure>
microenvironment, each of these sub-circuits is connected with signals originating from other cells in the tumor microenvironment. (Hanahan and Wienberg [44]. With permission from Elsevier)

As cancer progression involves alterations in signaling pathways due to mutations in the relevant genes, it is satisfying and mechanistically well-founded that a therapeutic intervention taking into account this biology of the affected cells can pave the way for a very effective cancer treatment [45,46]. Further, it has been established in clinical practice that targeting a single intermediate or pathway brings considerable results toward recovery, possibly because it impedes the synergistic signaling process of disease progression. Yet, the constitutive activation of a molecular event that contributes to cancer development can be sustained by different mechanisms, and strategies to inhibit multiple targets or redundant pathways simultaneously with molecular-targeted agents could prove to be an even more effective way to treat cancer and overcome resistance in cancer therapy [47]. Targeted drug therapy is the form of cancer therapeutics that targets specific genes and proteins of cancer cell reprogramming, the signaling molecules, and others in the tumor microenvironment that contribute to cancer development. This contrast with the single-target approach employed in chemotherapy to primarily target and kill actively dividing cancer cells with serious side effects and so the emergence of targeted drug therapy can be seen as a natural outcome of decades of studies on molecular reprogramming of affected cells in different cancers. Some noticeable breakthroughs have come in certain cancers as a renewed understanding of the signaling pathways underlying cancer development has led to the development of specific targeted drugs that have really revolutionized the treatment of cancer. This form of cancer therapy can be thoroughly optimized by means of precision oncology that enables taking advantage of genomic profiling of patient samples for insights into the mutational changes underlying pathway alterations responsible for cancer initiation and progression [48]. Precision oncology-based treatment strategies pledge to diagnose and prognosis the disease using specific molecular-level information about a patient's tumor to treat the ill with desired results. In this way, it qualifies to be a theranostic approach to cancer treatment satisfactorily. The term, theranostics literally means a combination of diagnosis and therapeutics and refers to the pairing of diagnostic methods such as the proteogenomics approach to biomarker discovery, with appropriate therapeutic interventions for effective management of the disease. Theranostics focuses on patient-centered care and thus provides a transition from conventional to personalized medicine for targeted, efficient and safe pharmacotherapy relevantly applicable in precision oncology [49,50].

The anticancer drugs employed in targeted therapy are mainly designed to target selected molecules directly involved with cancer cell signaling or those in the tumor microenvironment essentially required for tumor growth and cancer manifestation [51]. They are broadly classified as monoclonal antibodies (mAbs) and small-molecule drugs. The small molecule drugs are designed to directly approach the cell membrane and interact with targets inside the cell and usually inhibit the enzymatic activity of target proteins such as the proteasome complex, cyclin-dependent kinases and a variety of signaling proteins( Suppl. 1 & 2). Kinase family proteins such as tyrosine kinases, Rho kinase, Bruton tyrosine kinase, ABL kinases, NAK kinases, etc. play an essential role in modulating signaling pathways associated with cancer progression and therefore constitute a valuable source of biological targets against cancers (Table 1).

A type of targeted therapy, called tumor-agnostic therapy uses drugs and other substances to target cancer-specific genetic changes or markers to treat the problem without requiring focusing on the cancer type or where the disease may have started in the body. Therapeutic targeting of DNA damage response (DDR) signaling is another emerging field of targeted cancer therapy that exploits the options of targeting cancer cells with exceeding deficiencies in homologous recombination (HR) signaling which includes BRCA-mutated cancers. Poly(ADP-ribose) polymerase (PARP) and Inhibitors of poly(ADP-ribose) glycohydrolase (PARG) are the most important DNA repair enzymes that work synergistically in many different DDR pathways, including base excision repair, non-homologous end joining, nucleotide excision repair, homologous recombination (HR), maintenance of replication fork stability and nucleosome remodeling. These enzymes are essentially involved in the process of single-strand break (SSB) repair whose failure leads to the conversion of SSB into double-strand breaks (DSB) requiring repair by HR to prevent cell death. Such lethal genetic interactions, known as synthetic lethality, can be exploited to develop anticancer therapeutics and the enzymes of DDR signaling fit the needs satisfactorily. Overexpression of these proteins has been witnessed in different cancer types such as pancreatic, prostate, breast,
microenvironment, each of these sub-circuits is connected with signals originating from other cells in the tumor microenvironment. (Hanahan and Wienberg [44]. With permission from Elsevier)

As cancer progression involves alterations in signaling pathways due to mutations in the relevant genes, it is satisfying and mechanistically well-founded that a therapeutic intervention taking into account this biology of the affected cells can pave the way for a very effective cancer treatment [45,46]. Further, it has been established in clinical practice that targeting a single intermediate or pathway brings considerable results toward recovery, possibly because it impedes the synergistic signaling process of disease progression. Yet, the constitutive activation of a molecular event that contributes to cancer development can be sustained by different mechanisms, and strategies to inhibit multiple targets or redundant pathways simultaneously with molecular-targeted agents could prove to be an even more effective way to treat cancer and overcome resistance in cancer therapy [47]. Targeted drug therapy is the form of cancer therapeutics that targets specific genes and proteins of cancer cell reprogramming, the signaling molecules, and others in the tumor microenvironment that contribute to cancer development. This contrast with the single-target approach employed in chemotherapy to primarily target and kill actively dividing cancer cells with serious side effects and so the emergence of targeted drug therapy can be seen as a natural outcome of decades of studies on molecular reprogramming of affected cells in different cancers. Some noticeable breakthroughs have come in certain cancers as a renewed understanding of the signaling pathways underlying cancer development has led to the development of specific targeted drugs that have really revolutionized the treatment of cancer. This form of cancer therapy can be thoroughly optimized by means of precision oncology that enables taking advantage of genomic profiling of patient samples for insights into the mutational changes underlying pathway alterations responsible for cancer initiation and progression [48]. Precision oncology-based treatment strategies pledge to diagnose and prognosis the disease using specific molecular-level information about a patient's tumor to treat the ill with desired results. In this way, it qualifies to be a theranostic approach to cancer treatment satisfactorily. The term, theranostics literally means a combination of diagnosis and therapeutics and refers to the pairing of diagnostic methods such as the proteogenomics approach to biomarker discovery, with appropriate therapeutic interventions for effective management of the disease. Theranostics focuses on patient-centered care and thus provides a transition from conventional to personalized medicine for targeted, efficient and safe pharmacotherapy relevantly applicable in precision oncology [49,50].

The anticancer drugs employed in targeted therapy are mainly designed to target selected molecules directly involved with cancer cell signaling or those in the tumor microenvironment essentially required for tumor growth and cancer manifestation [51]. They are broadly classified as monoclonal antibodies (mAbs) and small-molecule drugs. The small molecule drugs are designed to directly approach the cell membrane and interact with targets inside the cell and usually inhibit the enzymatic activity of target proteins such as the proteasome complex, cyclin-dependent kinases and a variety of signaling proteins( Suppl. 1 & 2). Kinase family proteins such as tyrosine kinases, Rho kinase, Bruton tyrosine kinase, ABL kinases, NAK kinases, etc. play an essential role in modulating signaling pathways associated with cancer progression and therefore constitute a valuable source of biological targets against cancers (Table 1).

A type of targeted therapy, called tumor-agnostic therapy uses drugs and other substances to target cancer-specific genetic changes or markers to treat the problem without requiring focusing on the cancer type or where the disease may have started in the body. Therapeutic targeting of DNA damage response (DDR) signaling is another emerging field of targeted cancer therapy that exploits the options of targeting cancer cells with exceeding deficiencies in homologous recombination (HR) signaling which includes BRCA-mutated cancers. Poly(ADP-ribose) polymerase (PARP) and Inhibitors of poly(ADP-ribose) glycohydrolase (PARG) are the most important DNA repair enzymes that work synergistically in many different DDR pathways, including base excision repair, non-homologous end joining, nucleotide excision repair, homologous recombination (HR), maintenance of replication fork stability and nucleosome remodeling. These enzymes are essentially involved in the process of single-strand break (SSB) repair whose failure leads to the conversion of SSB into double-strand breaks (DSB) requiring repair by HR to prevent cell death. Such lethal genetic interactions, known as synthetic lethality, can be exploited to develop anticancer therapeutics and the enzymes of DDR signaling fit the needs satisfactorily. Overexpression of these proteins has been witnessed in different cancer types such as pancreatic, prostate, breast,
ovarian, and oral cancers, providing scope for inhibiting PARP activity as an effective therapeutic strategy. PARP and PARG inhibitors have shown improved results in different forms of tumors, and are under investigation for being used in combination therapy safely. [52,53].

The therapeutic mAbs are modified monoclonal antibodies that target antigens found on the cancer cells or cytotoxic T-lymphocytes in targeted cancer therapy. mAbs are important in cancer treatment as they may be exploited for potentiating the natural immune system by successfully mutualizing changes in immunogenicity of the affected cells during oncogenesis. The mAbs may be designed to coat the cancer cells to be opsonized and destroyed by the immune cell, block the activity of different cancer-specific antigens called neoantigens, generated by cancer cells, or inhibit the activities of immune checkpoint proteins that promote immune evasion in cancer development [54,55]. Several immune checkpoint proteins are expressed by immune cells, such as T cells, and cancer cells capable of binding with other partner proteins to help cancer cells escape immune responses. Their activation limits vital immune cell activities like T-cell infiltration and other effector cell functions resulting in tumor formation. CTLA-4 is a checkpoint protein present on the T-cell surface that binds to another protein called B7, preventing T cells from killing other target cells, including cancer cells. Certain mAbs, also called anti-CTLA4 monoclonal antibodies, are used to block CTLA-4 and are widely used as immune checkpoint inhibitors in a variety of human cancers. Different forms of monoclonal antibody-based therapy have proven to be efficacious in cancer treatment and are becoming increasingly important tools in targeted cancer therapy [56,57]. Importantly, cancer cells express a number of protein antigens that can be recognized by cytotoxic T lymphocyte (CTL) T cells, thus providing means for CTL-mediated cancer therapy. Targeting transformed cells by CTL may be crucial to the prevention of both hematological and solid tumors and its roles are being explored in cancer immunotherapy. T-cell transfer therapy, also called adoptive immunotherapy or immune cell therapy is a new form of cancer treatment designed to exploit enhanced anti-tumor immune response of the tumor antigen-specific CTL found in the tumors, and has been tried against neoantigen- possessing cells effectively in recent times. Two types of T-cell transfer therapy, tumor-infiltrating lymphocytes or TIL therapy and CAR T-cell therapy are in use, and both involve harvesting autologous T cells infiltrated into the tumor, growing large numbers of these cells in vitro, and administering to the patient for desired results. CAR T- cell therapy is similar to TIL therapy except that the T cells are designed to express a type of protein known as CAR (CAR for chimeric antigen receptor) to target specific antigens expressed in cancer cells in the body. Although CAR T cells have significantly improved the landscape for hematological malignancies, it has shown limited results in solid tumors as the solid tumors present certain obvious barriers to adoptive T-cell transfer and localization, but a variety of approaches are being deliberated to overcome these barriers to increase its specificity, efficacy, and safety in the treatment of different malignancies. The development of CAR T cell therapy for solid tumors has been impaired also because most target antigens are common with normal cells. Research is being directed to develop a ‘toolbox’ of novel chimeric antigen receptors (CARs) that could be programmed to use logic to discriminate between normal and cancerous cells to prevent toxicity. This development could help to overcome some of the barriers to the application of CAR-T cells against solid tumors [58]. Furthermore, therapeutic cancer vaccines, such as the dendritic cell (DC) vaccine, peptide vaccine, and RNA-based neoantigen vaccines have been developed for inducing CTLs against the antigens in cancer patients and have shown encouraging results. These vaccines can be designed to induce the production of biomolecules capable of targeting the shared antigens expressed by cancer cells through appropriate immune response and, are being investigated for their efficacy as neoantigen-targeted individualized cancer vaccines. Dendritic cells(DCs) are specialized Antigen-presenting cells (APCs) known for their ability to present antigens to T cells, and this property of DCs has been exploited for their application in therapeutic cancer vaccines which have been shown to induce protective anti-tumor activities [59]. Besides that, the transposable elements (REs) usually present in the tumor microenvironment are of potential therapeutic importance to create a pan-cancer vaccine that can aid in the prevention of a range of cancers. There is an enumerable number of regions with TEs involved with the expression of proteins in the cancer cell. Many of these are shared across tumors of the same type and could provide means for destruction by the immune system. The goal of immunotherapy remains to activate the individual's own immune system against the evolving tumors to successfully target the transformed cells with high selectivity, low toxicity, and appropriate results. Thus, immunotherapy remains the frontline area of targeted cancer therapies, and precision oncology will be focused on immunotherapy accordingly.
ovarian, and oral cancers, providing scope for inhibiting PARP activity as an effective therapeutic strategy. PARP and PARG inhibitors have shown improved results in different forms of tumors, and are under investigation for being used in combination therapy safely. [52,53].

The therapeutic mAbs are modified monoclonal antibodies that target antigens found on the cancer cells or cytotoxic T-lymphocytes in targeted cancer therapy. mAbs are important in cancer treatment as they may be exploited for potentiating the natural immune system by successfully mutualizing changes in immunogenicity of the affected cells during oncogenesis. The mAbs may be designed to coat the cancer cells to be opsonized and destroyed by the immune cell, block the activity of different cancer-specific antigens called neoantigens, generated by cancer cells, or inhibit the activities of immune checkpoint proteins that promote immune evasion in cancer development [54,55]. Several immune checkpoint proteins are expressed by immune cells, such as T cells, and cancer cells capable of binding with other partner proteins to help cancer cells escape immune responses. Their activation limits vital immune cell activities like T-cell infiltration and other effector cell functions resulting in tumor formation. CTLA-4 is a checkpoint protein present on the T-cell surface that binds to another protein called B7, preventing T cells from killing other target cells, including cancer cells. Certain mAbs, also called anti-CTLA4 monoclonal antibodies, are used to block CTLA-4 and are widely used as immune checkpoint inhibitors in a variety of human cancers. Different forms of monoclonal antibody-based therapy have proven to be efficacious in cancer treatment and are becoming increasingly important tools in targeted cancer therapy [56,57]. Importantly, cancer cells express a number of protein antigens that can be recognized by cytotoxic T lymphocyte (CTL) T cells, thus providing means for CTL-mediated cancer therapy. Targeting transformed cells by CTL may be crucial to the prevention of both hematological and solid tumors and its roles are being explored in cancer immunotherapy. T-cell transfer therapy, also called adoptive immunotherapy or immune cell therapy is a new form of cancer treatment designed to exploit enhanced anti-tumor immune response of the tumor antigen-specific CTL found in the tumors, and has been tried against neoantigen- possessing cells effectively in recent times. Two types of T-cell transfer therapy, tumor-infiltrating lymphocytes or TIL therapy and CAR T-cell therapy are in use, and both involve harvesting autologous T cells infiltrated into the tumor, growing large numbers of these cells in vitro, and administering to the patient for desired results. CAR T- cell therapy is similar to TIL therapy except that the T cells are designed to express a type of protein known as CAR (CAR for chimeric antigen receptor) to target specific antigens expressed in cancer cells in the body. Although CAR T cells have significantly improved the landscape for hematological malignancies, it has shown limited results in solid tumors as the solid tumors present certain obvious barriers to adoptive T-cell transfer and localization, but a variety of approaches are being deliberated to overcome these barriers to increase its specificity, efficacy, and safety in the treatment of different malignancies. The development of CAR T cell therapy for solid tumors has been impaired also because most target antigens are common with normal cells. Research is being directed to develop a ‘toolbox’ of novel chimeric antigen receptors (CARs) that could be programmed to use logic to discriminate between normal and cancerous cells to prevent toxicity. This development could help to overcome some of the barriers to the application of CAR-T cells against solid tumors [58]. Furthermore, therapeutic cancer vaccines, such as the dendritic cell (DC) vaccine, peptide vaccine, and RNA-based neoantigen vaccines have been developed for inducing CTLs against the antigens in cancer patients and have shown encouraging results. These vaccines can be designed to induce the production of biomolecules capable of targeting the shared antigens expressed by cancer cells through appropriate immune response and, are being investigated for their efficacy as neoantigen-targeted individualized cancer vaccines. Dendritic cells(DCs) are specialized Antigen-presenting cells (APCs) known for their ability to present antigens to T cells, and this property of DCs has been exploited for their application in therapeutic cancer vaccines which have been shown to induce protective anti-tumor activities [59]. Besides that, the transposable elements (REs) usually present in the tumor microenvironment are of potential therapeutic importance to create a pan-cancer vaccine that can aid in the prevention of a range of cancers. There is an enumerable number of regions with TEs involved with the expression of proteins in the cancer cell. Many of these are shared across tumors of the same type and could provide means for destruction by the immune system. The goal of immunotherapy remains to activate the individual's own immune system against the evolving tumors to successfully target the transformed cells with high selectivity, low toxicity, and appropriate results. Thus, immunotherapy remains the frontline area of targeted cancer therapies, and precision oncology will be focused on immunotherapy accordingly.
A major concern in cancer therapeutics is the proper drug delivery to the affected cells and tissue for the desired outcomes. Conventional chemotherapeutics may possess some serious side effects due to nonspecific targeting or inability to enter the core of the tumors, resulting in impaired treatment and a low survival rate. Researchers have been trying to address the issue with more specific methods of drug delivery including the use of nanotechnology in cancer therapeutics. Nanoparticles (NP)-based systems can be programmed to recognize cancerous cells for selective and accurate drug delivery with increased drug localization, cellular uptake, and bioavailability, avoiding encounters with healthy cells. The newly developed quantum dots (QDs) are the class of heterogeneous fluorescent nanoparticle, nanoscale materials with sizes ranging from 1 to 10 nm, with unique optical properties and optimal surface chemical properties to link with targets such as antibodies, peptides, and other small molecule drugs. Named so as the photoluminescent nanostructures can have fully quantized energy states with superior fluorescence characteristics, they are thought to be more specific and effective methods with wide applications in the diagnostics and molecular targeting of the transformed cells. The NP-based drug delivery system, in general, displays better pharmacokinetic and pharmacodynamic profiles including efficient targeting of cancer cells and reduction in side effects, they are sure to serve the needs of precision oncology-based therapy satisfactorily [60,61]. Further, antibody-drug conjugates (ADC) are a fast-expanding therapeutic strategy designed to selectively deliver drugs to cancer cells. ADCs are monoclonal antibodies linked with small molecule cytotoxic drugs through a chemical linker capable of approaching the cancer cells and attaching to the specific tumor antigens on the cell surface for direct drug delivery sparing healthy cells in the surroundings. They are designed to exploit the features of antigen-antibody specificity for efficient drugdelivery and are considered to be the magic bullets in targeted cancer therapy [62, 63]. In this way, precision oncology seems to be the best fit for strategizing effective means of targeted drug therapy by exploiting the genomic peculiarities of individuals or a cohort of patients for effective personalized cancer treatment. It will remain dedicated to studying the genetic profile of cancer cells to gain a thorough understanding of the alterations in key signaling pathways and related molecular events during cancer progression, therapy resistance, and recurrence to help improve targeted cancer therapy (Fig. 2).

<figure><img src="image_3.png" /><figcaption>**Figure 2.** Therapeutic Targeting of the Hallmarks of Cancer
Therapeutic agents that can mitigate the acquired capabilities necessary for tumor growth and cancer progression</figcaption></figure>
A major concern in cancer therapeutics is the proper drug delivery to the affected cells and tissue for the desired outcomes. Conventional chemotherapeutics may possess some serious side effects due to nonspecific targeting or inability to enter the core of the tumors, resulting in impaired treatment and a low survival rate. Researchers have been trying to address the issue with more specific methods of drug delivery including the use of nanotechnology in cancer therapeutics. Nanoparticles (NP)-based systems can be programmed to recognize cancerous cells for selective and accurate drug delivery with increased drug localization, cellular uptake, and bioavailability, avoiding encounters with healthy cells. The newly developed quantum dots (QDs) are the class of heterogeneous fluorescent nanoparticle, nanoscale materials with sizes ranging from 1 to 10 nm, with unique optical properties and optimal surface chemical properties to link with targets such as antibodies, peptides, and other small molecule drugs. Named so as the photoluminescent nanostructures can have fully quantized energy states with superior fluorescence characteristics, they are thought to be more specific and effective methods with wide applications in the diagnostics and molecular targeting of the transformed cells. The NP-based drug delivery system, in general, displays better pharmacokinetic and pharmacodynamic profiles including efficient targeting of cancer cells and reduction in side effects, they are sure to serve the needs of precision oncology-based therapy satisfactorily [60,61]. Further, antibody-drug conjugates (ADC) are a fast-expanding therapeutic strategy designed to selectively deliver drugs to cancer cells. ADCs are monoclonal antibodies linked with small molecule cytotoxic drugs through a chemical linker capable of approaching the cancer cells and attaching to the specific tumor antigens on the cell surface for direct drug delivery sparing healthy cells in the surroundings. They are designed to exploit the features of antigen-antibody specificity for efficient drugdelivery and are considered to be the magic bullets in targeted cancer therapy [62, 63]. In this way, precision oncology seems to be the best fit for strategizing effective means of targeted drug therapy by exploiting the genomic peculiarities of individuals or a cohort of patients for effective personalized cancer treatment. It will remain dedicated to studying the genetic profile of cancer cells to gain a thorough understanding of the alterations in key signaling pathways and related molecular events during cancer progression, therapy resistance, and recurrence to help improve targeted cancer therapy (Fig. 2).

<figure><img src="image_3.png" /><figcaption>**Figure 2.** Therapeutic Targeting of the Hallmarks of Cancer
Therapeutic agents that can mitigate the acquired capabilities necessary for tumor growth and cancer progression</figcaption></figure>
are being developed for clinical use in treating different cancer types. These drugs are being developed in clinical trials to target each of the emerging neoplastic characteristics and the enabling hallmarks capabilities towards effective cancer therapy. The listed drugs are just illustrative examples; there is a deep pipeline of investigational drugs in development to target different signaling molecules that lead to the hallmark capabilities. (Hanahan and Wienberg [44]. With permission from Elsevier)

Recent advances in cancer genomics and single-cell technologies have certainly made targeted therapy the accepted form of cancer treatment, and yet a huge amount of investment will be needed for future research, drug discovery, and diagnostics to fully unlock its potential and for their application in the management of cancer. Let us not forget that the socioeconomic burden of cancer remains high as the treatment options for most common cancers have been limited so far and is an indication for a renewed approach to expedite drug development to bring effective anticancer agents from bench to bedside in a cost-effective manner. The lack of understanding of the genetic heterogeneity of individual cancers has traditionally been limiting the search for efficacious agents for cancer treatment and missing a wide range of possibly suitable agents from other disease areas. The use of molecular characterization of different cancer types through cancer genomics can help resolve drug-related issues to a reasonable extent by repurposing the use of certain existing drugs as anticancer agents for a wide range of applications, and it will remain at the forefront of precision oncology [64,65]. Moreover, the move from tissue-based cancer- specific treatments to genome-based targeted treatments entails the reuse of anticancer drugs prescribed for one type of cancer to treat other cancer types as well. It is envisaged that, with the ever-greater understanding of cell signaling mechanisms and genetic alterations in carcinogenesis, considerable progress in cancer treatment will be realized in the near future. Considering that academia, industries, and civil society will be working in tandem to cater to the contemporary needs of the system, it is hoped that a wide range of people with cancer will benefit from this new development in cancer research in the future to benefit the system as a whole [66,67].

**5. Conclusion**

Genome-based cancer therapies propose developing treatments that target the specific molecular features of an individual's tumor instead of targeting common features of cancer to find a cure. Genomic databases produced as part of different cancer initiatives now provide a large amount of information on mutation profiles with significant genetic associations with diseases to facilitate targeted molecular therapies. Furthermore, an in-depth understanding of the genetic composition and heterogeneity of an individual's tumor is now becoming possible using single-cell technologies. This should help individuals successfully get the right treatment at the right time without requiring them to undergo more generalized treatment with excessive side effects. Importantly, drug resistance has traditionally been a serious problem in cancer treatment, but the emergence of targeted drug therapy based on precision oncology can greatly improve outcomes. Advances in genetic detection methods, liquid biopsy, and single-cell sequencing technology could facilitate deciphering the molecular mechanism of tumor drug resistance to help develop updated and effective anticancer agents in response to drug resistance. All of these developments in fact reflect natural outcomes of cancer genome research, the level of support coming from multi-omics platforms is very encouraging and is on path to satisfactorily achieve the intended goal of the cancer initiatives. The growing success of this form of treatment is sure to further strengthen our belief in the possibility of effective cancer treatment over time.

**Declarations:**

**Acknowledgements:** I acknowledge the consistent departmental support received from the School of Bio Sciences & Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India, leading to the completion of this work with time.
are being developed for clinical use in treating different cancer types. These drugs are being developed in clinical trials to target each of the emerging neoplastic characteristics and the enabling hallmarks capabilities towards effective cancer therapy. The listed drugs are just illustrative examples; there is a deep pipeline of investigational drugs in development to target different signaling molecules that lead to the hallmark capabilities. (Hanahan and Wienberg [44]. With permission from Elsevier)

Recent advances in cancer genomics and single-cell technologies have certainly made targeted therapy the accepted form of cancer treatment, and yet a huge amount of investment will be needed for future research, drug discovery, and diagnostics to fully unlock its potential and for their application in the management of cancer. Let us not forget that the socioeconomic burden of cancer remains high as the treatment options for most common cancers have been limited so far and is an indication for a renewed approach to expedite drug development to bring effective anticancer agents from bench to bedside in a cost-effective manner. The lack of understanding of the genetic heterogeneity of individual cancers has traditionally been limiting the search for efficacious agents for cancer treatment and missing a wide range of possibly suitable agents from other disease areas. The use of molecular characterization of different cancer types through cancer genomics can help resolve drug-related issues to a reasonable extent by repurposing the use of certain existing drugs as anticancer agents for a wide range of applications, and it will remain at the forefront of precision oncology [64,65]. Moreover, the move from tissue-based cancer- specific treatments to genome-based targeted treatments entails the reuse of anticancer drugs prescribed for one type of cancer to treat other cancer types as well. It is envisaged that, with the ever-greater understanding of cell signaling mechanisms and genetic alterations in carcinogenesis, considerable progress in cancer treatment will be realized in the near future. Considering that academia, industries, and civil society will be working in tandem to cater to the contemporary needs of the system, it is hoped that a wide range of people with cancer will benefit from this new development in cancer research in the future to benefit the system as a whole [66,67].

**5. Conclusion**

Genome-based cancer therapies propose developing treatments that target the specific molecular features of an individual's tumor instead of targeting common features of cancer to find a cure. Genomic databases produced as part of different cancer initiatives now provide a large amount of information on mutation profiles with significant genetic associations with diseases to facilitate targeted molecular therapies. Furthermore, an in-depth understanding of the genetic composition and heterogeneity of an individual's tumor is now becoming possible using single-cell technologies. This should help individuals successfully get the right treatment at the right time without requiring them to undergo more generalized treatment with excessive side effects. Importantly, drug resistance has traditionally been a serious problem in cancer treatment, but the emergence of targeted drug therapy based on precision oncology can greatly improve outcomes. Advances in genetic detection methods, liquid biopsy, and single-cell sequencing technology could facilitate deciphering the molecular mechanism of tumor drug resistance to help develop updated and effective anticancer agents in response to drug resistance. All of these developments in fact reflect natural outcomes of cancer genome research, the level of support coming from multi-omics platforms is very encouraging and is on path to satisfactorily achieve the intended goal of the cancer initiatives. The growing success of this form of treatment is sure to further strengthen our belief in the possibility of effective cancer treatment over time.

**Declarations:**

**Acknowledgements:** I acknowledge the consistent departmental support received from the School of Bio Sciences & Technology, Vellore Institute of Technology, Vellore, Tamil Nadu, India, leading to the completion of this work with time.
**Ethics approval and consent to participate:** Not Applicable

**Consent for publication:** Not applicable

**Competing interests:** Not applicable

**Funding:** Not applicable

**Authors' contributions:** Not applicable

**Availability of data and materials:** Kumar, Manish (2024). Precision Oncology, Cell Signaling and Targeted Therapy: A Holistic Approach to Molecular Cancer Therapeutics. figshare. Dataset. https://doi.org/10.6084/m9 figshare.25594059

**References:**

1. Loftus LV, Amend SR, Pienta KJ. Interplay between Cell Death and Cell Proliferation Reveals New Strategies for Cancer Therapy. International Journal of Molecular Sciences. 2022; 23(9):4723. https://doi.org/10.3390/ijms23094723

2. Takeshima, H., Ushijima, T. Accumulation of genetic and epigenetic alterations in normal cells and cancer risk. npj Precis. Onc. 3, 7 (2019). https://doi.org/10.1038/s41698-019-0079-

3. You JS, Jones PA. Cancer genetics and epigenetics: two sides of the same coin? Cancer Cell. 2012 Jul 10;22(1):9-20. doi: 10.1016/j.ccr.2012.06.008. PMID: 22789535; PMCID: PMC3396881.

4. Advani D, Sharma S, Kumari S, Ambasta RK, Kumar P. Precision Oncology, Signaling, and Anticancer Agents in Cancer Therapeutics. Anticancer Agents Med Chem. 2022;22(3):433-468. doi: 10.2174/1871520621666210308101029. PMID: 33687887.

5. Tsimberidou AM, Fountzilas E, Nikanjam M, Kurzrock R. Review of precision cancer medicine: Evolution of the treatment paradigm. Cancer Treat Rev. 2020 Jun;86:102019. doi: 10.1016/j.ctrv.2020.102019. Epub 2020 Mar 31. PMID: 32251926; PMCID: PMC7272286.

6. van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C. Ten years of next-generation sequencing technology. Trends Genet. 2014 Sep;30(9):418-26. doi: 10.1016/j.tig.2014.07.001. Epub 2014 Aug 6. PMID: 25108476.

7. Feitelson MA, Arzumanyan A, Kulathinal RJ, Blain SW, Holcombe RF, Mahajna J, Marino M, Martinez-Chantar ML, Nawroth R, Sanchez-Garcia I, Sharma D, Saxena NK, Singh N, Vlachostergios PJ, Guo S, Honoki K, Fujii H, Georgakilas AG, Bilsland A, Amedei A, Niccolai E, Amin A, Ashraf SS, Boosani CS, Guha G, Ciriolo MR, Aquilano K, Chen S, Mohammed SI, Azmi AS, Bhakta D, Halicka D, Keith WN, Nowsheen S. Sustained proliferation in cancer: Mechanisms and novel therapeutic targets. Semin Cancer Biol. 2015 Dec;35 Suppl(Suppl):S25-S54. doi: 10.1016/j.semcancer.2015.02.006. Epub 2015 Apr 17. PMID: 25892662; PMCID: PMC4898971.

8. Sivaraman K, Muthukumar K, Shanthi C. A potential bioactive peptide candidate for biomaterial and tissue engineering applications. Life Sci. 2019 Jun 1;226:140-148. doi: 10.1016/j.lfs.2019.04.010. Epub 2019 Apr 12. PMID: 30986446.

9. Geeleher P, Huang RS. Exploring the Link between the Germline and Somatic Genome in Cancer. Cancer
**Ethics approval and consent to participate:** Not Applicable

**Consent for publication:** Not applicable

**Competing interests:** Not applicable

**Funding:** Not applicable

**Authors' contributions:** Not applicable

**Availability of data and materials:** Kumar, Manish (2024). Precision Oncology, Cell Signaling and Targeted Therapy: A Holistic Approach to Molecular Cancer Therapeutics. figshare. Dataset. https://doi.org/10.6084/m9 figshare.25594059

**References:**

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2. Takeshima, H., Ushijima, T. Accumulation of genetic and epigenetic alterations in normal cells and cancer risk. npj Precis. Onc. 3, 7 (2019). https://doi.org/10.1038/s41698-019-0079-

3. You JS, Jones PA. Cancer genetics and epigenetics: two sides of the same coin? Cancer Cell. 2012 Jul 10;22(1):9-20. doi: 10.1016/j.ccr.2012.06.008. PMID: 22789535; PMCID: PMC3396881.

4. Advani D, Sharma S, Kumari S, Ambasta RK, Kumar P. Precision Oncology, Signaling, and Anticancer Agents in Cancer Therapeutics. Anticancer Agents Med Chem. 2022;22(3):433-468. doi: 10.2174/1871520621666210308101029. PMID: 33687887.

5. Tsimberidou AM, Fountzilas E, Nikanjam M, Kurzrock R. Review of precision cancer medicine: Evolution of the treatment paradigm. Cancer Treat Rev. 2020 Jun;86:102019. doi: 10.1016/j.ctrv.2020.102019. Epub 2020 Mar 31. PMID: 32251926; PMCID: PMC7272286.

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7. Feitelson MA, Arzumanyan A, Kulathinal RJ, Blain SW, Holcombe RF, Mahajna J, Marino M, Martinez-Chantar ML, Nawroth R, Sanchez-Garcia I, Sharma D, Saxena NK, Singh N, Vlachostergios PJ, Guo S, Honoki K, Fujii H, Georgakilas AG, Bilsland A, Amedei A, Niccolai E, Amin A, Ashraf SS, Boosani CS, Guha G, Ciriolo MR, Aquilano K, Chen S, Mohammed SI, Azmi AS, Bhakta D, Halicka D, Keith WN, Nowsheen S. Sustained proliferation in cancer: Mechanisms and novel therapeutic targets. Semin Cancer Biol. 2015 Dec;35 Suppl(Suppl):S25-S54. doi: 10.1016/j.semcancer.2015.02.006. Epub 2015 Apr 17. PMID: 25892662; PMCID: PMC4898971.

8. Sivaraman K, Muthukumar K, Shanthi C. A potential bioactive peptide candidate for biomaterial and tissue engineering applications. Life Sci. 2019 Jun 1;226:140-148. doi: 10.1016/j.lfs.2019.04.010. Epub 2019 Apr 12. PMID: 30986446.

9. Geeleher P, Huang RS. Exploring the Link between the Germline and Somatic Genome in Cancer. Cancer
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14. Li, Y., Kang, K., Krahn, J.M. et al. A comprehensive genomic pan-cancer classification using The Cancer Genome Atlas gene expression data. BMC Genomics 18, 508 (2017). https://doi.org/10.1186/s12864-017-3906-0

15. Krogan NJ, Lippman S, Agard DA, Ashworth A, Ideker T. The cancer cell map initiative: defining the hallmark networks of cancer. Mol Cell. 2015 May 21;58(4):690-8. doi: 10.1016/j.molcel.2015.05.008. PMID: 26000852; PMCID: PMC5359018.

16. Zheng F, Kelly MR, Ramms DJ, Heintschel ML, Tao K, Tutuncuoglu B, Lee JJ, Ono K, Foussard H, Chen M, Herrington KA, Silva E, Liu SN, Chen J, Churas C, Wilson N, Kratz A, Pillich RT, Patel DN, Park J, Kuenzi B, Yu MK, Licon K, Pratt D, Kreisberg JF, Kim M, Swaney DL, Nan X, Fraley SI, Gutkind JS, Krogan NJ, Ideker T. Interpretation of cancer mutations using a multiscale map of protein systems. Science. 2021 Oct;374(6563):eabf3067. doi: 10.1126/science.abf3067. Epub 2021 Oct 1. PMID: 34591613; PMCID: PMC9126298.

17. Tsherniak A, Vazquez F, Montgomery PG, Weir BA, Kryukov G, Cowley GS, Gill S, Harrington WF, Pantel S, Krill-Burger JM, Meyers RM, Ali L, Goodale A, Lee Y, Jiang G, Hsiao J, Gerath WFJ, Howell S, Merkel E, Ghandi M, Garraway LA, Root DE, Golub TR, Boehm JS, Hahn WC. Defining a Cancer Dependency Map. Cell. 2017 Jul 27;170(3):564-576.e16. doi: 10.1016/j.cell.2017.06.010. PMID: 28753430; PMCID: PMC5667678.

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10. Scacheri CA, Scacheri PC. Mutations in the noncoding genome. Curr Opin Pediatr. 2015 Dec;27(6):659-64. doi: 10.1097/MOP.0000000000000283. PMID: 26382709; PMCID: PMC5084913.

11. Cancer Genome Atlas Research Network, Weinstein JN, Collisson EA, Mills GB, Shaw KR, Ozenberger BA, Ellrott K, Shmulevich I, Sander C, Stuart JM. The Cancer Genome Atlas Pan-Cancer analysis project. Nat Genet. 2013 Oct;45(10):1113-20. doi: 10.1038/ng.2764. PMID: 24071849; PMCID: PMC3919969.

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14. Li, Y., Kang, K., Krahn, J.M. et al. A comprehensive genomic pan-cancer classification using The Cancer Genome Atlas gene expression data. BMC Genomics 18, 508 (2017). https://doi.org/10.1186/s12864-017-3906-0

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17. Tsherniak A, Vazquez F, Montgomery PG, Weir BA, Kryukov G, Cowley GS, Gill S, Harrington WF, Pantel S, Krill-Burger JM, Meyers RM, Ali L, Goodale A, Lee Y, Jiang G, Hsiao J, Gerath WFJ, Howell S, Merkel E, Ghandi M, Garraway LA, Root DE, Golub TR, Boehm JS, Hahn WC. Defining a Cancer Dependency Map. Cell. 2017 Jul 27;170(3):564-576.e16. doi: 10.1016/j.cell.2017.06.010. PMID: 28753430; PMCID: PMC5667678.

18. Pacini C, Duncan E, Gonçalves E, Gilbert J, Bhosle S, Horswell S, Karakoc E, Lightfoot H, Curry E, Muyas F, Bouaboula M, Pedamallu CS, Cortes-Ciriano I, Behan FM, Zalmas LP, Barthorpe A, Francies H, Rowley S, Pollard J, Beltrao P, Parts L, Iorio F, Garnett MJ. A comprehensive clinically informed map of dependencies in cancer cells and framework for target prioritization. Cancer Cell. 2024 Feb 12;42(2):301-316.e9. doi: 10.1016/j.ccell.2023.12.016. Epub 2024 Jan 11. PMID: 38215750.

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<caption>Table 1. List of Protein Kinase Inhibitors approved by FDA.</caption>

(NRY, non-receptor protein-tyrosine kinase; RTK, receptor protein-tyrosine kinase; S/T, protein-serine/threonine kinase; T/Y, dual-specificity protein kinase)

<table><thead><tr><td>Protein kinase inhibitor</td><td>Approval year</td><td>Primary targets</td><td>Target kinase family</td><td>Indications</td></tr></thead><tbody><tr><td>Abemaciclib</td><td>2017</td><td>CDK4/6</td><td>S/T</td><td>Breast cancer</td></tr><tr><td>Acalabrutinib</td><td>2017</td><td>BTK</td><td>NRY</td><td>Lymphoma</td></tr><tr><td>Afatinib</td><td>2013</td><td>ErbB1/2/4</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Alectinib</td><td>2015</td><td>ALK, RET</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Avapritinib</td><td>2020</td><td>PDGFR</td><td>RTK</td><td>Gastrointestinal Cancer</td></tr><tr><td>Axitinib</td><td>2012</td><td>VEGFR1/2/3</td><td>RTK</td><td>Kidney cancer</td></tr><tr><td>Binimetinib</td><td>2018</td><td>MEK1/2</td><td>T/Y</td><td>Melanoma</td></tr><tr><td>Bosutinib</td><td>2012</td><td>BCR-Abl</td><td>NRY</td><td>Leukemia</td></tr><tr><td>Brigatinib</td><td>2017</td><td>ALK</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Cabozantinib</td><td>2012</td><td>RET, VEGFR2</td><td>RTK</td><td>Thyroid. kidney, hepatocellular cancer</td></tr><tr><td>Capmatinib hydrochloride</td><td>2020</td><td>c-MET</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Ceritinib</td><td>2014</td><td>ALK</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Cobimetinib</td><td>2015</td><td>MEK1/2</td><td>T/Y</td><td>Melanoma</td></tr><tr><td>Crizotinib</td><td>2011</td><td>ALK, ROS1</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Dabrafenib</td><td>2013</td><td>B-Raf</td><td>S/T</td><td>Melanoma; lung, thyroid Cancer</td></tr><tr><td>Dacomitinib</td><td>2018</td><td>EGFR</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Dasatinib</td><td>2006</td><td>BCR-Abl</td><td>NRY</td><td>Leukemia</td></tr><tr><td>Encorafenib</td><td>2018</td><td>B-Raf</td><td>S/T</td><td>Melanoma, colorectal cancer</td></tr><tr><td>Entrectinib</td><td>2019</td><td>TRKA/B/C, ROS1</td><td>RTK</td><td>Lung cancer; solidTumors</td></tr><tr><td>Erdafitinib</td><td>2019</td><td>FGFR1/2/3/4</td><td>RTK</td><td>Urothelial carcinoma</td></tr></tbody></table>
<caption>Table 1. List of Protein Kinase Inhibitors approved by FDA.</caption>

(NRY, non-receptor protein-tyrosine kinase; RTK, receptor protein-tyrosine kinase; S/T, protein-serine/threonine kinase; T/Y, dual-specificity protein kinase)

<table><thead><tr><td>Protein kinase inhibitor</td><td>Approval year</td><td>Primary targets</td><td>Target kinase family</td><td>Indications</td></tr></thead><tbody><tr><td>Abemaciclib</td><td>2017</td><td>CDK4/6</td><td>S/T</td><td>Breast cancer</td></tr><tr><td>Acalabrutinib</td><td>2017</td><td>BTK</td><td>NRY</td><td>Lymphoma</td></tr><tr><td>Afatinib</td><td>2013</td><td>ErbB1/2/4</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Alectinib</td><td>2015</td><td>ALK, RET</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Avapritinib</td><td>2020</td><td>PDGFR</td><td>RTK</td><td>Gastrointestinal Cancer</td></tr><tr><td>Axitinib</td><td>2012</td><td>VEGFR1/2/3</td><td>RTK</td><td>Kidney cancer</td></tr><tr><td>Binimetinib</td><td>2018</td><td>MEK1/2</td><td>T/Y</td><td>Melanoma</td></tr><tr><td>Bosutinib</td><td>2012</td><td>BCR-Abl</td><td>NRY</td><td>Leukemia</td></tr><tr><td>Brigatinib</td><td>2017</td><td>ALK</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Cabozantinib</td><td>2012</td><td>RET, VEGFR2</td><td>RTK</td><td>Thyroid. kidney, hepatocellular cancer</td></tr><tr><td>Capmatinib hydrochloride</td><td>2020</td><td>c-MET</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Ceritinib</td><td>2014</td><td>ALK</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Cobimetinib</td><td>2015</td><td>MEK1/2</td><td>T/Y</td><td>Melanoma</td></tr><tr><td>Crizotinib</td><td>2011</td><td>ALK, ROS1</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Dabrafenib</td><td>2013</td><td>B-Raf</td><td>S/T</td><td>Melanoma; lung, thyroid Cancer</td></tr><tr><td>Dacomitinib</td><td>2018</td><td>EGFR</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Dasatinib</td><td>2006</td><td>BCR-Abl</td><td>NRY</td><td>Leukemia</td></tr><tr><td>Encorafenib</td><td>2018</td><td>B-Raf</td><td>S/T</td><td>Melanoma, colorectal cancer</td></tr><tr><td>Entrectinib</td><td>2019</td><td>TRKA/B/C, ROS1</td><td>RTK</td><td>Lung cancer; solidTumors</td></tr><tr><td>Erdafitinib</td><td>2019</td><td>FGFR1/2/3/4</td><td>RTK</td><td>Urothelial carcinoma</td></tr></tbody></table>
<table><tr><td>Erlotinib hydrochloride</td><td>2004</td><td>EGFR</td><td>RTK</td><td>Lung, Pancreatic cancer</td></tr><tr><td>Everolimus</td><td>2009</td><td>FKBP12/mTOR</td><td>S/T</td><td>Breast, kidney cancer, Neuroendocrine tumors</td></tr><tr><td>Fedratinib</td><td>2019</td><td>JAK2</td><td>NRY</td><td>Myelofibrosis</td></tr><tr><td>Futibatinib</td><td>2022</td><td>FGFR2</td><td>RTK</td><td>Cholangiocarcinomas</td></tr><tr><td>Gefitinib</td><td>2003</td><td>EGFR</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Gilteritinib</td><td>2018</td><td>Flt3</td><td>RTK</td><td>Leukemia</td></tr><tr><td>Ibrutinib</td><td>2013</td><td>BTK</td><td>NRY</td><td>Lymphoma</td></tr><tr><td>Imatinib mesylate</td><td>2001</td><td>BCR-Abl</td><td>NRY</td><td>Leukemia; Gastrointestinal</td></tr><tr><td>Infigratinib</td><td>2021</td><td>FGFRs</td><td>RTK</td><td>Cholangiocarcinoma</td></tr><tr><td>Lapatinib ditosylate</td><td>2007</td><td>ErbB1/2/HER2</td><td>RTK</td><td>Breast cancer</td></tr><tr><td>Larotrectinib</td><td>2018</td><td>TRKA/B/C</td><td>RTK</td><td>Solid tumors</td></tr><tr><td>Lenvatinib</td><td>2015</td><td>VEGFR, RET</td><td>RTK</td><td>Hepatocellular, endometrial, Thyroid, Kidney cancer</td></tr><tr><td>Lorlatinib</td><td>2018</td><td>ALK</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Midostaurin</td><td>2017</td><td>Flt3</td><td>RTK</td><td>Leukemia</td></tr><tr><td>Mobocertinib</td><td>2021</td><td>EGFR with exon 20 insertions</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Neratinib</td><td>2017</td><td>ErbB2/HER2</td><td>RTK</td><td>Breast cancer</td></tr><tr><td>Nilotinib</td><td>2007</td><td>BCR-Abl</td><td>NRY</td><td>Leukemia</td></tr><tr><td>Osimertinib</td><td>2015</td><td>EGFR T790M</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Pacritinib</td><td>2022</td><td>JAK2</td><td>RTK</td><td>Myelofibrosis</td></tr><tr><td>Palbociclib</td><td>2015</td><td>CDK4/6</td><td>S/T</td><td>Breast cancer</td></tr><tr><td>Pazopanib hydrochloride</td><td>2009</td><td>VEGFR1/2/3</td><td>RTK</td><td>Kidney cancer; soft tissue sarcoma</td></tr><tr><td>Pemigatinib</td><td>2020</td><td>FGFR2</td><td>RTK</td><td>Cholangiocarcinoma</td></tr></table>
<table><tr><td>Erlotinib hydrochloride</td><td>2004</td><td>EGFR</td><td>RTK</td><td>Lung, Pancreatic cancer</td></tr><tr><td>Everolimus</td><td>2009</td><td>FKBP12/mTOR</td><td>S/T</td><td>Breast, kidney cancer, Neuroendocrine tumors</td></tr><tr><td>Fedratinib</td><td>2019</td><td>JAK2</td><td>NRY</td><td>Myelofibrosis</td></tr><tr><td>Futibatinib</td><td>2022</td><td>FGFR2</td><td>RTK</td><td>Cholangiocarcinomas</td></tr><tr><td>Gefitinib</td><td>2003</td><td>EGFR</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Gilteritinib</td><td>2018</td><td>Flt3</td><td>RTK</td><td>Leukemia</td></tr><tr><td>Ibrutinib</td><td>2013</td><td>BTK</td><td>NRY</td><td>Lymphoma</td></tr><tr><td>Imatinib mesylate</td><td>2001</td><td>BCR-Abl</td><td>NRY</td><td>Leukemia; Gastrointestinal</td></tr><tr><td>Infigratinib</td><td>2021</td><td>FGFRs</td><td>RTK</td><td>Cholangiocarcinoma</td></tr><tr><td>Lapatinib ditosylate</td><td>2007</td><td>ErbB1/2/HER2</td><td>RTK</td><td>Breast cancer</td></tr><tr><td>Larotrectinib</td><td>2018</td><td>TRKA/B/C</td><td>RTK</td><td>Solid tumors</td></tr><tr><td>Lenvatinib</td><td>2015</td><td>VEGFR, RET</td><td>RTK</td><td>Hepatocellular, endometrial, Thyroid, Kidney cancer</td></tr><tr><td>Lorlatinib</td><td>2018</td><td>ALK</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Midostaurin</td><td>2017</td><td>Flt3</td><td>RTK</td><td>Leukemia</td></tr><tr><td>Mobocertinib</td><td>2021</td><td>EGFR with exon 20 insertions</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Neratinib</td><td>2017</td><td>ErbB2/HER2</td><td>RTK</td><td>Breast cancer</td></tr><tr><td>Nilotinib</td><td>2007</td><td>BCR-Abl</td><td>NRY</td><td>Leukemia</td></tr><tr><td>Osimertinib</td><td>2015</td><td>EGFR T790M</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Pacritinib</td><td>2022</td><td>JAK2</td><td>RTK</td><td>Myelofibrosis</td></tr><tr><td>Palbociclib</td><td>2015</td><td>CDK4/6</td><td>S/T</td><td>Breast cancer</td></tr><tr><td>Pazopanib hydrochloride</td><td>2009</td><td>VEGFR1/2/3</td><td>RTK</td><td>Kidney cancer; soft tissue sarcoma</td></tr><tr><td>Pemigatinib</td><td>2020</td><td>FGFR2</td><td>RTK</td><td>Cholangiocarcinoma</td></tr></table>
<table><tr><td>Pexidartinib</td><td>2019</td><td>CSF1R</td><td>RTK</td><td>Tenosynovial giant cell tumor</td></tr><tr><td>Pirtobrutinib</td><td>2023</td><td>BTK</td><td>NRY</td><td>Lymphoma</td></tr><tr><td>Ponatinib hydrochloride</td><td>2012</td><td>BCR-Abl</td><td>NRY</td><td>Leukemia</td></tr><tr><td>Pralsetinib</td><td>2020</td><td>RET</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Quizartinib</td><td>2023</td><td>FLT3/STK1</td><td>RTK</td><td>Leukemia</td></tr><tr><td>Regorafenib</td><td>2012</td><td>VEGFR1/2/3</td><td>RTK</td><td>Gastrointestinal, Colorectal, Hepatocellular cancer</td></tr><tr><td>Ribociclib</td><td>2017</td><td>CDK4/6</td><td>S/T</td><td>Breast cancer</td></tr><tr><td>Ripretinib</td><td>2020</td><td>KIT/PDGFR</td><td>RTK</td><td>Gastrointestinal cancer</td></tr><tr><td>Ruxolitinib phosphate</td><td>2011</td><td>JAK1/2/3, Tyk</td><td>NRY</td><td>Myelofibrosis</td></tr><tr><td>Selpercatinib</td><td>2020</td><td>RET</td><td>RTK</td><td>Lung, thyroid cancer</td></tr><tr><td>Selumetinib</td><td>2020</td><td>MEK1/2</td><td>T/Y</td><td>Neurofibroma</td></tr><tr><td>Sorafenib tosylate</td><td>2005</td><td>VEGFR1/2/3</td><td>RTK</td><td>Thyroid, Kidney, Hepatocellular cancer</td></tr><tr><td>Sunitinib malate</td><td>2006</td><td>VEGFR2</td><td>RTK</td><td>Gastrointestinal, kidney, pancreatic cancer</td></tr><tr><td>Temsirolimus</td><td>2007</td><td>FKBP12/mTOR</td><td>S/T</td><td>kidney cancer</td></tr><tr><td>Tepotinib</td><td>2021</td><td>Met</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Tivozanib</td><td>2021</td><td>VEGFR2</td><td>RTK</td><td>kidney cancer</td></tr><tr><td>Trametinib</td><td>2013</td><td>MEK1/2</td><td>T/Y</td><td>Melanoma</td></tr><tr><td>Trilaciclib</td><td>2021</td><td>CDK4/6</td><td>S/T</td><td>Lung cancer</td></tr><tr><td>Tucatinib</td><td>2020</td><td>ErbB2/HER2</td><td>RTK</td><td>Breast cancer</td></tr><tr><td>Vandetanib</td><td>2011</td><td>VEGFR2</td><td>RTK</td><td>Thyroid cancer</td></tr><tr><td>Vemurafenib</td><td>2011</td><td>B-Raf</td><td>S/T</td><td>Melanoma; histiocytic sarcoma</td></tr><tr><td>Zanubrutinib</td><td>2019</td><td>BTK</td><td>NRY</td><td>Lymphoma</td></tr></table>
<table><tr><td>Pexidartinib</td><td>2019</td><td>CSF1R</td><td>RTK</td><td>Tenosynovial giant cell tumor</td></tr><tr><td>Pirtobrutinib</td><td>2023</td><td>BTK</td><td>NRY</td><td>Lymphoma</td></tr><tr><td>Ponatinib hydrochloride</td><td>2012</td><td>BCR-Abl</td><td>NRY</td><td>Leukemia</td></tr><tr><td>Pralsetinib</td><td>2020</td><td>RET</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Quizartinib</td><td>2023</td><td>FLT3/STK1</td><td>RTK</td><td>Leukemia</td></tr><tr><td>Regorafenib</td><td>2012</td><td>VEGFR1/2/3</td><td>RTK</td><td>Gastrointestinal, Colorectal, Hepatocellular cancer</td></tr><tr><td>Ribociclib</td><td>2017</td><td>CDK4/6</td><td>S/T</td><td>Breast cancer</td></tr><tr><td>Ripretinib</td><td>2020</td><td>KIT/PDGFR</td><td>RTK</td><td>Gastrointestinal cancer</td></tr><tr><td>Ruxolitinib phosphate</td><td>2011</td><td>JAK1/2/3, Tyk</td><td>NRY</td><td>Myelofibrosis</td></tr><tr><td>Selpercatinib</td><td>2020</td><td>RET</td><td>RTK</td><td>Lung, thyroid cancer</td></tr><tr><td>Selumetinib</td><td>2020</td><td>MEK1/2</td><td>T/Y</td><td>Neurofibroma</td></tr><tr><td>Sorafenib tosylate</td><td>2005</td><td>VEGFR1/2/3</td><td>RTK</td><td>Thyroid, Kidney, Hepatocellular cancer</td></tr><tr><td>Sunitinib malate</td><td>2006</td><td>VEGFR2</td><td>RTK</td><td>Gastrointestinal, kidney, pancreatic cancer</td></tr><tr><td>Temsirolimus</td><td>2007</td><td>FKBP12/mTOR</td><td>S/T</td><td>kidney cancer</td></tr><tr><td>Tepotinib</td><td>2021</td><td>Met</td><td>RTK</td><td>Lung cancer</td></tr><tr><td>Tivozanib</td><td>2021</td><td>VEGFR2</td><td>RTK</td><td>kidney cancer</td></tr><tr><td>Trametinib</td><td>2013</td><td>MEK1/2</td><td>T/Y</td><td>Melanoma</td></tr><tr><td>Trilaciclib</td><td>2021</td><td>CDK4/6</td><td>S/T</td><td>Lung cancer</td></tr><tr><td>Tucatinib</td><td>2020</td><td>ErbB2/HER2</td><td>RTK</td><td>Breast cancer</td></tr><tr><td>Vandetanib</td><td>2011</td><td>VEGFR2</td><td>RTK</td><td>Thyroid cancer</td></tr><tr><td>Vemurafenib</td><td>2011</td><td>B-Raf</td><td>S/T</td><td>Melanoma; histiocytic sarcoma</td></tr><tr><td>Zanubrutinib</td><td>2019</td><td>BTK</td><td>NRY</td><td>Lymphoma</td></tr></table>