bluuebunny/crossref_metadata_2025 huggingface dataset:
Prospective validation of the IRSN-23 model for personalized chemotherapy and proposal of new breast cancer subtype classification.
Authors: Sota Yoshiaki , Seno Shigeto , Naoi Yasuto , Honma Keichiro , Shimoda Masafumi , Tanei Tomonori , Matsuda Hideo , Shimazu Kenzo
Published: August 2023

10

Background: The IRSN-23 model uses DNA microarray analysis of tumor tissue to stratify patients into highly sensitive (Gp-R) or less sensitive (Gp-NR) chemotherapy groups based on immune-related gene expression. In a previous report (n=901), Gp-R showed a 39% pCR rate, while Gp-NR had 11% (P=4.98E-23; Sota, Y., et al., Annals of Oncology 25.1 (2014): 100-106). This study aimed to evaluate the reproducibility of the IRSN-23 model in prospective independent validation cohorts and investigate its clinical significance and impact on breast cancer subtype classification. Methods: Tumor tissues were obtained from 143 breast cancer patients undergoing preoperative chemotherapy at Osaka University Hospital (OUH). Patients were classified into Gp-R or Gp-NR using the IRSN-23 model, and its ability to predict pathological complete response (pCR) was assessed. Results were validated with independent public datasets (n=965; breast cancer (n=919) and rectal cancer (n=46)). Results: In the OUH prospective cohort, the pCR rate was significantly higher in the Gp-R group (29.3% (11/41)) than in the Gp-NR group (1.4% (1/71)) without trastuzumab (P=1.70E-5). In all prospective validation cohorts without anti-HER2 therapy, the pCR rate in the Gp-R group was significantly higher than in the Gp-NR group. Pooled analysis of the prospective validation set revealed higher pCR rates in the Gp-R group than in the Gp-NR group, both without (Gp-R 41.9% (104/248) vs. Gp-NR 13.6% (50/367), P=4.0E-15) and with (Gp-R 48.3% (57/118) vs. Gp-NR 35.5% (66/186), P=0.03) anti-HER2 therapy (Table). Collaborative analyses of IRSN-23 Immune Score (IS) and OncotypeDx Recurrence Score (RS) suggested the identification of a highly sensitive chemotherapy group (pCR%; IS>-25+RS>25: 21.6% vs. IS ≤ 25 + RS > 25: 2.9%, P=1.13E-04). PAM50 as an attack factor and IRSN-23 as a defense factor capture the tumor microenvironment, suggesting a new subtype classification of breast cancer. Conclusions: This study offers prospective validation of the IRSN-23 model in predicting chemotherapy efficacy, exhibiting high reproducibility. The findings indicate the IRSN-23 model is clinically valuable and propose new breast cancer subtype classification. These results hold significant implications for personalized treatment strategies.[Table: see text]
Identifying gaps and challenges faced in lesbian, gay, bisexual, transgender, queer, intersex and asexual (LGBTQIA+) adolescent and young adults (AYA) cancer care: A scoping review.
Authors: Thaarun Thirumeninathan , Heng E Han , Poon Eileen Yi Ling
Published: August 2023

100

Background: There is a dearth of evidence related to the needs and challenges faced by LGBTQIA+AYA cancer patients and survivors. This scoping review aims to summarize the existing literature about the challenges faced, the nature and currently available services provided for LGBTQIA+ AYA cancer patients and survivors. Methods: In February 2023, a systematic keyword search was conducted on PubMed and Embase. This included the terms, “AYA”, “Adolescent and Young Adults”, “Cancer”, “LGBTQIA+”, “Sexual and Gender Minorities”, “obstacles”, “biases” and “challenges”. The studies selected were screened for further relevant cited references. Papers exploring LGBTQIA+ AYA (ages 15-49) challenges and available services were selected. Exclusion criteria included studies that lacked AYA-specific results, or did not report on challenges/difficulties faced. Included studies were then thematically analyzed according to challenges, available services and help required. Qualitative analysis was subsequently performed. Results: A total of 202 studies were identified. We excluded 185 studies based on the exclusion criteria. 17 studies were included in this review. 7 challenges, 7 help service gaps and 3 available services were identified in LGBTQIA+ AYA cancer care. Major challenges reported include LGBTQIA+ inclusive understanding of psychosocial needs, depression/anxiety, disclosure of sexual and gender minority status to Healthcare Providers (HCPs) and the recognition of partners by HCPs. Deficient services included LGBTQIA+-specific support groups and cultural competence training amongst HCPs. Frameworks are currently being developed to enhance HCP-patient relationships and improve the inclusivity of marginalized LGBTQIA+ patients in the healthcare system. However, the exact available services were unreported or not specific to this population. Conclusions: This review underlined the lack of LGBTQIA+-AYA-specific evidence regarding challenges faced by patients and survivors. While domains relating to mental health outcomes are increasingly reported in the literature, others including identity formation, financial outcomes and fertility needs continue to be underreported. There is also an absence of research on Asian populations and less developed countries. Further research is required to understand and address these specific gaps and difficulties. This is necessary to provide holistic AYA care to improve compliance, and also ensure better cancer treatment and survivorship experiences.
The use of machine learning models to predict PFS and OS outcomes from waterfall plots in randomized clinical trials (MAP-OUTCOMES).
Authors: Alshankati Khadjah , Alshibany Aisha , Toma Augustin , Lajkosz Katherine , Wang Bo , Haibe-Kains Benjamin , Siu Lillian L.
Published: August 2023

107

Background: Depth of tumor response (DepOR) of individual patients, as visualized by waterfall plots, is an emerging short-term endpoint that may represent a surrogate for survival-based outcomes such as PFS and OS. We hypothesize that the configuration of waterfall plots in randomized trials may predict PFS/OS outcomes. Methods: A literature-based search was performed for all phase II/III randomized clinical trials published in MEDLINE from 2010 to 2022 testing molecularly targeted agents (MTA) or immunotherapy (IO). Articles reporting at least 1 waterfall plot for each treatment arm depicting maximum DepOR of target lesions with corresponding PFS/OS Kaplan-Meier plots were included. Studies are defined as positive or negative based on the achievement of a priori stated primary endpoint. Trial data collected included sample size per arm, cancer type, mechanisms of action of drug(s) tested, line of treatment, etc. Images of waterfall plots were manually extracted from publications and then processed through a semi-automatic extraction process using WebPlotDigitizer and Tesseract to produce tabular representations. Logistic regression with L2 regularization was used for modeling; hyperparameter tuning was accomplished with five-fold cross-validation on a training set compromising 80% of the data. Results: A total of 111 studies were identified: 65 (59%) phase III and 46 (41%) phase II, mean sample size per arm 317 (19-1581). Most frequent cancer type was gastrointestinal 24 (22%). MTA, IO and combinations were tested in 113 (51%), 35(16%) and 11 (5%) studies respectively. Chemotherapy and other treatment regimens were used in 63 (28%) trials. PFS was the primary endpoint in 62 (56%); 80 (75%) studies were positive. Of the 111 studies only 83 (75%) were retained for machine learning analysis, the remainder were excluded due to atypical formatting such as superimposed waterfall plots. Performance of the model was assessed on a test set which comprised 20% of the original dataset. Table below shows the classification metrics from modelling. Both PPV and NPV were ≥80%. Conclusions: MAP-OUTCOMES evaluated pan-cancer randomized studies with diverse therapeutic anticancer agents. It is a computational tool with the potential to predict survival-based outcomes from waterfall plots and may help with decisions regarding follow-on randomized studies. Further validation is ongoing. [Table: see text]
mICKEY: Memory-efficient deep learning for personalized biomarker discovery and cancer origin prediction from DNA methylation data.
Authors: Jantrachotechatchawan Chanati , Tussanapirom Pakanan , Aewsrisakul Kasidech , Leephatarakit Natthawadee , Duangrattanalert Kobchai
Published: August 2023

109

Background: Carcinoma of unknown primary (CUP) accounts for up to 5% of all cancer cases and presents challenges in identifying primary cancer sites and successful treatment. DNA methylation abnormalities on the 5'-cytosine-phosphate-guanine-3' (CpG) motif across the genome are associated with carcinogenesis, enabling their use as cancer biomarkers for early diagnosis and tissue origin prediction. This study proposes a Combined Approach for 1) CpG site selection, 2) predicting cancer origin and identifying biomarkers, and 3) developing an open-source application for user-friendly data analysis. Methods: To emulate the state-like progression of cancer and accommodate missing values, discretized methylation beta values and missing values were tokenized. Feature selection using L1 regularization of lambda 0.0003 resulted in 152 CpG sites out of an initial set of 312,792. Three independent sets were selected for each of the 3 self-attention type: vanilla scaled dot-product, dense synthesizer, and factorized dense synthesizer. Self-attention enhances the biomarker discovery approach toward personalization as it generates a unique attention map for each sample input that highlights essential features for primary site prediction. A permutation test further evaluated contribution by the selected CpG sites, confirming biomarkers identification for each primary site. An open-source application was developed to predict cancer origin using methylation beta values, providing a user-friendly interface displaying predicted primary sites and corresponding percentages. Results: Independent sets of selected CpG performs comparably to the initial set with robustness (most well above 97% in precision, recall, and F1) across different clinical (sample type: normal, primary, metastatic, recurrent; and AJCC pathologic stage) and demographic groups (age, gender, race). The model identifies important biomarkers previously shown in literatures i.e. GATA4 and HOXD. Conclusions: This study offers valuable insights into feature selection, primary site prediction, and biomarker discovery using DNA methylation data, with potential practical applications for healthcare facilities and in personalized cancer treatment.
Systematic mapping of gender disparities in oncology publications of north African countries: The GEORGiNA study.
Authors: El Bairi Khalid ,   GEORGiNA study collaborators
Published: August 2023

112

Background: Gender Inequities in cancer academic research continue to be a challenging global issue, including in low- and middle-income countries. While North African research environment has been historically perceived as “male-dominant”, research on gender inequity in this region is largely lacking. GEORGiNA (“Gender Equity in Oncology Research” Group in North Africa) is a bibliometric study focusing on gender disparities aiming at portraying the current situation and inform policy-making to deliver recommendations for gender equality. Methods: A bibliometric analysis based on Pubmed was conducted for the period 2018-2022. Eligible articles included at least one author from a North-African country as first or last position. Cancer researchers were asked to review the articles with the first/last author from their same country of origin, to accurately determine authors’ gender. A manual data extraction guide with simulation was developed and shared with all collaborators to harmonize data extraction, accuracy, and reporting. Factors associated with gender distribution were studied as appropriate. Results: A total of 4,414 articles published by North-African cancer researchers in the last 5 years were included in the final analysis. Females represented 52.5% of first authors, with a notable women’s presence in Tunisia (72.6% vs 27.4%). Morocco, Algeria, and Egypt reported fair distribution in this authorship (ratios ≈0.5) while Sudan and Libya had male dominance (62% and 70%, respectively). Among 23,984 of coauthors, 45% were females and 19% of all publications had no female co-authors. Last authorships were significantly more common for male researchers, in all countries (p < 0.001). Of interest, women’s lead authorships appeared markedly increased over last years, including during the period of COVID-19 outbreak. Original articles presented more commonly last authors who were men (62.6% vs 37.4% women) (p < 0.001). Indeed, male last authors had received more funding than females and published more open access research (p = 0.018). Conversely, disclosure of the funding source was more common for original contributions led by women as first authors (p < 0.001). Male authors (first and last positions) were more involved in international collaborations as compared to female authors in similar positions (p < 0.001). There was association between a reduced number of female co-authors and men in last authorship positions (p < 0.001). On the other hand, when women were first authors, female co-authors resulted substantially higher (p < 0.001). Conclusions: Women in North-African cancer research publications seem to be fairly positioned, albeit differences still exist. Lack of funding and limited engagement in international collaborations are still prevalent barriers for women scientists. The preliminary findings from the GEORGiNA study can catalyze progress toward gender equity.
Explainable machine learning to inform real-world evidence: A case study on small cell lung cancer survival analysis.
Authors: Marzano Luca , Darwich Adam S. , Dan Asaf , Tendler Salomon , Raghotama Jayanth , Lewensohn Rolf , De Petris Luigi , Meijer Sebastiaan
Published: August 2023

113

Background: In recent years, machine learning algorithms for survival analysis have been developed as an alternative to traditional Cox regression. Despite the good performances, these are viewed as black box models that lack interpretability, which may limit their clinical applications. There has been a growing interest in explaining and interpreting machine learning models, which has led to the emergence of the field of explainable artificial intelligence (XAI). However, few studies have focused on how these methods could be of benefit to survival analysis of real-world healthcare data. Methods: In this study, we explored the use of current XAI techniques to analyze the effects of platinum doublet chemotherapy on small cell lung cancer patients in developed machine learning models.The analyzed data included real-world patients treated at Karolinska University Hospital (n=570) and three phase III randomized clinical trials shared by the Project Data Sphere initiative (n=987). The real-world data covariates included were age, sex, TNM staging, ECOG performance status, lab values, brain metastasis, and concomitant radiotherapy. The aggregated dataset including the clinical trials contained the following variables: age, sex, performance status, brain metastasis, and protocol violations. Eight machine learning models were trained and compared with Cox regression. The performance of the models was evaluated using C-index, and the time variation of Brier Score and C/D AUC.Temporal feature importance and partial dependence were used to explore the overall covariate impact on overall survival (Global XAI). Ceteris-paribus and SurvShap(t) were used to investigate the covariate impact for the single patient prediction (local XAI). The models were firstly trained only on real-world data before aggregation with the clinical trials. Results: Ensemble machine learning provided the best performances. XAI techniques showed the potential to increase explainability of survival predictions in function of time. Global XAI showed the time range of the model reliability, trend inversions regarding treatment decisions and covariate importance along the time. Local XAI allowed to test the impact of covariates between long survival patients and the comparison between real-world and clinical trials. Conclusions: Our results demonstrate the potential of XAI techniques applied to survival machine learning and real-world data, thus providing insights into the mechanisms driving model predictions and demonstrate the utility of this approach in clinical research.
Quantification of timeloss within complex tumor therapies.
Authors: Martens Nora , Vogt Katharina , Eichler Ronny , Herzog Moritz , Illmer Thomas , Bornhäuser Martin , Folprecht Gunnar
Published: August 2023

126

Background: There are various studies on reducing the waiting time of tumor patients before therapy sessions. In this study, we investigated how much waiting time within therapy sessions occurs due to delayed administration of the next drug. In addition, digital documented infusion time of specific drugs were determined to calculate waiting time. Both metrics serve as an indication of the potential to improve the effectiveness and efficiency of the infusion process. Methods: The therapy sequence of preliminary 29 patients in the Outpatient Therapy Center of the University Hospital Dresden was investigated. PDF export of the prescriptions of all cycles of the patient with the documentation of the therapy sequences from BD Cato is performed. In python the extraction of all time stamps and the processing of all start and stop times of the medication administration took place. Based on this data, waiting time between infusions were calculated. In addition, analysis of the total administration time of the specific medication was performed. Results: This revealed a median of 23 minutes of patient waiting time between infusion sequences (n = 29 patients and 1154 measured infusion changes). We compared 7 specific medications to the intended infusion time, taking particular note of the high variance in duration. We postulate due to standard administration protocols that the infusion time variance indicates additional waiting time. Both metrics are only an indication, since other factors besides the waiting time can also influence the time between two infusions. Conclusions: Treatment time for the same therapy protocol varied widely between patients, both in terms of waiting time between infusions and in the duration of infusion compared to the intended infusion time. Both indicate the opportunity to improve efficiency, thus providing more hospital-free lifetime for patients and increase revenue and standardization for treatment centers.
Efficacy of a digital media platform to combat inequities in global oncology education.
Authors: Leyfman Yan , Menon Gayathri P. , Joshi Muskan , Pawar Shubhadarshini , Wilkerson William B. , Balasubramanian Maduri , Van de Kieft Alexandra , Park Chandler H.
Published: August 2023

132

Background: Social media has emerged as a powerful vehicle for the dissemination of medical information, especially in resource-limited regions, due to its mass global reach. However, 1/3 of social media posts contain misinformation with 76.9% of them containing harmful information leading to adverse outcomes that are a detriment to global public health. To address this, MedNews Week (MNW), a free, digital medical education platform dedicated to combating healthcare misinformation, was developed to contribute to global oncology education through biweekly programming. Its main show, Keynote Conference, features live virtual presentations from oncology’s premier global leaders discussing the latest developments in cancer before a mainstream global audience. The aim of this study was to assess the worldwide reach and impact of this cost-free, virtual oncology education platform. Methods: From January 2022 to 2023, MNW hosted 25 global oncology leaders as Keynote Speakers (Mean H-index=50.09). Viewership, impressions, and outreach data were collected from MNW’s social media accounts and TweepMaps. Data was analyzed to assess MNW’s global reach and engagement and stratified based on engagement sentiment, gender, age group, and occupation. Results: During this period, MNW generated a Healthcare Social Graph Score of 92.77% (top 7.33 percentile of global healthcare influencers) with over 109,128 Twitter impressions and 4,731 engagements reaching 1.9 million accounts globally over 12 months (Table). Most of the followers were from non-healthcare fields with slightly more males than females. Those who engaged conveyed positive sentiments (59.9% likes and 26.2% mentions) contributing to a viewership increase from 72,136 (6 months) to 157,559 (1 year). The platform reached 100 cities and 57 countries of which 16 were of low-to-middle socioeconomic (SE) status. Conclusions: MNW has demonstrated an ability to attract and sustain a diverse, global, growing audience. Given MNW’s continued growth, it provides an innovative model to engage and disseminate medical information to mainstream audiences. The platform’s ability to showcase global leaders to mainstream audiences gratuitously, especially in lower SE regions that have been historically underserved, offers a practical approach to combat educational inequity. Thus, MNW represents a novel approach with promising potential to positively impact global oncology education.[Table: see text]
Dexamethasone free antiemetic prophylaxis for highly emetogenic chemotherapy: A phase III, double-blind, randomized controlled trial.
Authors: Radhakrishnan Venkatraman , Venkatakrishnan Kritthivasan , Jayachandran Perumal Kalaiyarasi , Selvarajan Gangothri , Rajaraman Swaminathan
Published: August 2023

133

Background: Chemotherapy-induced nausea and vomiting (CINV) is a common side effect of highly emetogenic chemotherapy (HEC). Current guidelines recommend the use of dexamethasone (DEX) for prophylaxis, but the effectiveness and safety of a DEX-free regimen for CINV prophylaxis in HEC is not known. Methods: This was an investigator-initiated, double-blind, phase 3 RCT designed to show the non-inferiority of a DEX-free regimen (olanzapine, palonosetron, and fosaprepitant; OPF) compared to the NCCN recommended DEX-containing regimen (olanzapine, palonosetron, and dexamethasone; OPD). Chemotherapy-naive patients aged 18-80 years receiving single-day HEC were randomized 1:1 to receive either the OPD regimen (olanzapine 5 mg once a day on days 1-4, palonosetron 0.25 mg on day 1, and DEX 12 mg on day 1) or the OPF regimen (olanzapine and palonosetron as above, and fosaprepitant 150 mg on day 1).The primary endpoint was to compare complete response (CR) rates for vomiting (no vomiting and no rescue medication) during the overall phase (start of chemotherapy to 120 h). The secondary endpoints were CR for nausea (ESAS), toxicities (CTCAE), and patient reported outcome measures (PROM) using MDASI. 175 patients in each arm were required show non-inferiority (NI) of OPF regimen compared to OPD regiment with power of 90%, 2-sided alpha of 5%, and NI margin of 15%. Results: Between May 2022-Dec 2022, 350 patients were randomized and 346 received the study interventions (OPD arm n = 174 and OPF arm n = 172). The most common chemotherapy used was adriamycin/cyclophosphamide (66%) followed by cisplatin (27%). CR rates for vomiting for the overall phase were 48.8% in the OPD arm and 79.6% in the OPF arm (P < 0.001), with an absolute difference of -30.8% and 2-sided 95% CI = (-40.31, -21.24) which was within the pre-defined NI margin of 15% and also showed superiority. The DEX-free arm also had significantly higher CR rates for nausea and total control (vomiting and nausea combined) (Table). PROM for fatigue (P = 0.009) and drowsiness (P = 0.002) were more in the OPF arm in the acute phase, and insomnia (P < 0.001) in the OPD arm in the delayed phase. Global Health Status QOL score on day 6 in the OPD arm was 55.36 ± 16.15 and in the OPF arm was 57.84 ± 12.76, P = 0.11. Conclusions: This study shows that a DEX-free OPF regimen is superior to the DEX-based OPD regimen and should be considered a standard option for CINV prophylaxis for HEC. Clinical trial information: CTRI/2022/03/040906 . [Table: see text]
Deep learning-based characterization of the drug tolerant persister cell state in lung cancer.
Authors: Wu Wei , Cech Lauren , Olivas Victor , Zaman Aubhishek , Kerr Daniel Lucas , Bivona Trever G.
Published: August 2023

141

Background: Lung cancer is the leading cause of cancer-related lethality globally. Targeted therapies improve the clinical outcome of cancer treatment; however, a subpopulation of cancer cells survive during initial therapy and evolve into drug tolerant persister cells (DTPs) that maintain a residual disease reservoir. Residual disease preludes acquired resistance and tumor progression; therefore, identifying and eliminating DTPs could benefit future treatment paradigms. We have shown that Hippo pathway effector YAP1 (Yes Associated Protein-1) is activated in oncogene-driven lung cancers when cancer cells are exposed to various targeted therapies, such as EGFR, ALK, and RAS inhibitors. YAP1 transcriptional activation during targeted therapy is characterized by its increased nuclear localization and interaction with transcription factors. This activation promotes the expression of genes involved in cell survival, cellular plasticity, and metabolic reprogramming at the residual disease state. We hypothesized that detection of intrinsic or acquired persister cells may aid the development of optimized treatment regimens. In this study, we are building image-based deep learning models to identify YAP1 activation-mediated DTPs from histologically stained slides. Methods: H&E or YAP-stained immunohistochemistry (IHC) images from clinical lung cancer and patient-derived tumor xenograft samples were collected throughout targeted therapy and were annotated with semi-automation using high performance computing clusters. A deep learning model (U-Net algorithm) was used for image segmentation, training, validation, and testing. Results: 1638 images were annotated and over 80,000 patches from these images for YAP positive cells (or regions of interest) comprised the training dataset with semi-supervised automation. Subsequently, we built a customized deep-learning model to detect YAP-mediated DTP cell states from whole histopathological image slides. The deep learning-based model achieved excellent accuracy of 0.8238 and 0.9091 in training, and 0.8040 and 0.8949 in validation datasets for two different annotations, respectively. For a test dataset, the model obtained 0.81 and 0.902 accuracy for the two annotations, respectively. Conclusions: We have constructed a deep learning convolutional neural network model to infer the presence of the YAP1 activation-mediated drug tolerant persister cell state prior to or during targeted treatment of lung cancer. Implementing our AI-based model into routine lung cancer care in the future could identify patient subpopulations with YAP1 activated tumors who would most benefit from receiving YAP1-targeted small molecule inhibitors.
Efficacy and safety of pembrolizumab in advanced neuroendocrine tumors (NETs): A meta-analysis of clinical trials.
Authors: Chitkara Akshit , Patel Rushin , Anamika Fnu , Yang Chieh , Patel Zalak , Patel Femina , Patel Mrunal , Dhaliwal Jasninder , Ramaswamy Bhuvaneswari
Published: August 2023

165

Background: Patients with recurrent or metastatic neuroendocrine tumors (NETs) have limited treatment options and a poor prognoses. Programmed death–ligand 1 (PD-L1) has been associated with the pathogenesis, progression, and prognosis of NETs. This article analyzes the efficacy and safety profile of PDL1 inhibitor Pembrolizumab in advanced NETs. Our objective is to identify all the clinical trials in which Pembrolizumab has been assessed in treating NETs and to evaluate the efficacy and safety profile in this patient population with high power. Methods: Systemic searches of PubMed, the Cochrane Library, and ClinicalTrials.gov were conducted with prespecified terms. The outcomes studied in our analysis were objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and serious adverse events (AEs). We calculated the pooled ORR for these studies using weighted pooled ORR = Σ (ORR_i * weight_i). We calculated the standard error using the formula SE = √(Σ (wi x (1 - ORRi) x ORRi) / Σ (wi x ni)) and the 95% confidence interval using the formula CI = ORR ± (1.96 x SE). This statistical method was also used to calculate our study's pooled DCR, PFS, OS, and serious AEs. However, it is essential to note that the pooled data is only as reliable as the individual data estimates from each study and may be subject to bias or confounding factors. Results: Five clinical trials met the inclusion criteria, including patients with gastrointestinal, pancreatic, lung, and lower genital tract NETs. Outcome data were available for all five studies, comprising 177 patients with NETs who received Pembrolizumab as part of the treatment regimen (Table). The pooled ORR and DCR were 5.27% (95% CI 2.23-8.31) and 5.4% (95% CI 3-7.8), respectively. The pooled weighted PFS was 4.4 months, and pooled weighted OS was 23.3 months. These findings suggest that Pembrolizumab has a promising ORR, DCR, PFS, and OS. Safety was a secondary endpoint, and the pooled serious AEs were noted in 20.9% of patients. Conclusions: Pembrolizumab demonstrated statistically significant efficacy and safety profile in a subset of patients with NETs and was overall well-tolerated. In recent years, the combination strategy of tyrosine kinase inhibitors (TKI) with PDL-1 checkpoint inhibitors has shown promising clinical benefits in patients with various solid tumors. Further studies are needed to analyze the efficacy and safety of TKI with PD-L1 inhibitors in NETs. [Table: see text]
Topical diclofenac in prevention of capecitabine associated HFS in patients with breast cancer: An exploratory subgroup analysis of the D-ToRCH study.
Authors: Santhosh Akhil , Sharma Atul , Batra Atul , Gogia Ajay , Jha Akash , Pramanik Raja
Published: August 2023

18

Background: Hand foot syndrome (HFS) is a dose-limiting side effect of capecitabine in patients with breast cancer. Celecoxib, an oral cyclo-oxygenase-2 (COX-2) inhibitor is effective in reducing the incidence of capecitabine associated HFS. However, it has not been adopted in the clinics due to concerns regarding cardiac and gastrointestinal toxicity. We report the efficacy of topical diclofenac in prevention of capecitabine associated HFS in patients with breast cancer. Methods: In the D-ToRCH (Diclofenac-topical for reduction of capecitabine related HFS) trial, we randomized 264 patients with breast or gastrointestinal cancers planned to receive capecitabine to apply either 1% topical diclofenac or placebo gel. Stratified (male or female; capecitabine monotherapy or combination therapy), permuted variable size block randomization was done using a computer-generated random numbers sequence. The primary objective was to compare the incidence of grade 2 or higher HFS in diclofenac and placebo arms. Secondary objectives were incidence of any grade HFS, capecitabine dose reductions due to HFS and self-reported adherence with application. Here, we report the exploratory subgroup analysis of patients with breast cancer. Results: The breast cancer subgroup included 148 patients (77 in drug arm and 71 in placebo arm). Baseline characteristics were similar in both arms. Median age of overall population was 47 years (IQR 39-56). 89 patients (60.1%) had an ECOG (Eastern Co-operative Oncology Group) performance status of 0-1, while the rest had a score of 2. Hypothyroidism was the most common comorbidity (n=24, 16.2%). Majority received capecitabine monotherapy (n=95, 64.2%). The most common additional chemotherapy drug used was lapatinib (n=42, 79.3%). 60 patients had stage 3 disease (40.8%) and 88 patients had metastatic breast cancer (59.5%). Overall, 20 patients developed any grade HFS, of which 6 were in the diclofenac arm and 14 in placebo arm (7.8% vs 19.7%, p=0.034). Grade 2/3 HFS events were noted in 3 patients (3.9%) in diclofenac arm and 11 patients (15.5%) in placebo arm (p=0.016). Capecitabine dose reductions were less frequent in the diclofenac arm compared to placebo (3.9% vs 15.5%). Adherence to topical treatment was similar in both the study arm. Other adverse events of capecitabine like diarrhea, mucositis and myelosuppression were similar in both the arms. Conclusions: Topical diclofenac gel significantly reduced the incidence of all grades of HFS in breast cancer patients receiving capecitabine. Applying topical diclofenac led to less frequent capecitabine dose reductions. Moving forward, we feel this should be the new standard of care and use of topical diclofenac should be regularized in medical oncology outpatient departments. Clinical trial information: CTRI/2021/01/030592 .
Efficacy of PD-1 inhibitors in the treatment of advanced gastrointestinal tumors and the effect on T-lymphocyte subsets and IL-6 levels in patients.
Authors: He XinCheng , Hou Lei , Bai Jun , Sun Chao , Wang Dongjie , He Jinyao , He Li , An Gaili
Published: August 2023

44

Background: Immune checkpoint inhibitors (ICIs) have improved the therapeutic prospects in advanced gastrointestinal tumors. The PD-L1 expression has become one of predictive biomarkers for immunotherapy and used in treatment, but there are still some drawbacks. The aim of this study was to investigate the changes in peripheral blood T-lymphocyte subsets, IL-6 levels before and after treatment with ICIs and clinical significance. Methods: 70 patients with advanced gastrointestinal tumors who were hospitalized in Shaanxi Provincial People's Hospital from January 2020 to December 2022 were selected. 30 healthy patients were selected as controls. PD-L1 was detected by immunohistochemistry. Patients were treated with ICIs (sintilimab or pembrolizumab). 1 day before treatment, 20 days after the end of the 4 cycles of treatment, peripheral venous blood was collected and CT or MRI was performed to evaluate the therapeutic effect. Complete response (CR), partial response (PR), and stable disease (SD) were classified as immune response group, and progressive disease (PD) was classified as immune non-response group. To evaluate the effects of ICIs on the levels of T-lymphocyte subsets (Percentage of CD3+T cells, percentage of CD4+T cells, percentage of CD8+T cells, CD4+/CD8+, CD3+T cells, CD4+T cells, CD8+T cells) and IL-6. Results: Compared to controls, CD3+T cells, CD4+T cells, CD8+T cells and CD4+/CD8+ were significantly lower ( P<0.05). After 4 cycles of immunotherapy, the CD3+T cells, CD4+T cells, CD8+T cells, and CD4+/CD8+ levels were significantly higher ( P<0.05), and IL-6 levels were lower ( P<0.05). After 4 cycles of treatment, 48 cases were divided in the immune response group and 22 cases in the immune non-response group, with a treatment efficiency of 68.6%. In the immune response group compared to the immune non-response group, the levels of percentage of CD4+T cells, CD4+/CD8+, CD3+T cells and CD4+T cells were significantly higher ( P<0.05), while the percentage of CD8+T cells level was lower ( P<0.05). The percentage of CD4+T cells, CD4+/CD8+, CD3+T cells, CD4+T cells and CD8+T cells were significantly higher ( P<0.05) in the immune response group after 4 cycles of immunotherapy, while the percentage of CD8+T cells level was lower ( P<0.05) compared to before immunotherapy. The percentage of CD4+T cells and CD4+/CD8+ were significantly lower ( P<0.05), the percentage of CD8+T cells and CD8+T cells were higher ( P<0.05) in the immune non-response group compared to before immunotherapy. In the immune response group, the percentage of CD4+T cells was higher in the PD-L1 high expression groups (≥ 50%) compared to the PD-L1 low expression groups (< 50%) ( P<0.05). Conclusions: PD-1 inhibitors can affect the distribution of immune cells such as T-lymphocyte subsets in patients with advanced gastrointestinal tumors and improve the immune status of patients.
Progression free survival in patients of HCC on atezolizumab/bevacizumab in Pakistan.
Authors: Zafar Amjad , Niazi Zeeshan Ahmed Khan , Abdul Rashid Asma , Shakeel Nimra , Naqi Naeem , Aziz Zeba
Published: August 2023

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Background: Liver cancers had been the second leading cause of cancer related deaths, globally and hepatocellular carcinoma (HCC) accounts for 75-85% of the primary liver malignancies. Recently, the combination of Atezolizumab-Bevacizumab (atezo-beva) had been considered to be the standard of care for unresectable HCC. This study aims to assess the impact of the atezo-beva combination therapy on patients with HCC in Pakistan that will help to improve the standard of care and could lead to better health outcomes for our patients. Methods: A retrospective, uni-center study was conducted among the patients of HCC presented in the oncology department of Hameed Latif Hospital, Lahore, Pakistan, with the sample size of 46. The diagnosed patients of unresectable HCC were included. The combination of Atezolizumab 1200mg and Bevacizumab 15mg per kg were administered intravenous every 3 weekly. The therapeutic response to treatment was assessed by CT or MRI after 3 months of initiation of treatment as per Response Evaluation Criteria in Solid Tumors for immunotherapy (iRECIST). Results: A total of 46 participants were included with the median age of 61.5 years. 91.3% and 8.7% participants were male and female, respectively. Majority, 78.3% had viral etiology for HCC and the median level of alpha fetoprotein (AFP) was 99.43 ng/ml. The response to atezo-beva combination after 4 cycles of treatment was partial response (45.17%), progressive disease (15.2%), and stable disease (10.9%). Moreover, the current status of the participants was as ongoing treatment (67.4%), progressive disease (13.0%), drug side effects (6.5%), lost to follow up (6.5%) and mortality (6.5%). Conclusions: The effect of atezo-beva combination on unresectable HCC showed the majority to have partial response. However further studies are needed to validate these findings as well as to assess the PFS and OS of atezo-beva combination in Pakistani population.
Correlation of carbohydrate antigen 19-9 response with radiologic response and survival in intrahepatic cholangiocarcinoma: A prospective cohort study.
Authors: Wu Lu
Published: August 2023

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Background: Although Carbohydrate antigen 19-9 (CA19-9) showed promising prognostic value in patients with intrahepatic cholangiocarcinoma (iCCA), its role in response assessment remains unknown. We aimed to study the association of CA19-9 response (defined as > 50% reduction from baseline) with radiologic response, and its role in predicting outcome in patients with unresectable iCCA. Methods: A prospective cohort of 422 patients who were initially identified as unresectable iCCAs with baseline CA19-9 ≥ 100 U/mL and treated with systemic therapies at our institution between January 2017 and December 2021 was enrolled in this study. Radiologic response was assessed using the Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 criteria. A landmark assessment of CA19-9 response and radiologic response was made. The association between CA19-9 response and imaging response, progression-free survival (PFS), or overall survival (OS) were analyzed, respectively. Results: Two hundred and sixty-seven (63.3%) patients showed CA19-9 response. CA19-9 response was seen in 93.2% (123/132) of radiologic responders, and 49.7% (144/290) of radiologic non-responders, respectively (P < 0.001). CA19-9 responders outperformed non-responders in median PFS (10.6 vs 3.6 months, P < 0.001) or OS (21.4 vs 6.3 months, P < 0.001), respectively. The common independent predictors of both OS and PFS included distant metastasis, CA19-9 non-responder, and radiologic non-responder in multivariable analysis. Conclusions: CA19-9 response is a valuable addition to assess tumor response and associated with improved outcome of iCCAs. Achieving CA19-9 response should be one of the therapeutic aims of patients with iCCA who are managed with systemic therapies. The results of this study have first published online in Cancer 2023 Jul 14. doi: 10.1002/cncr.34854 .
The safety of robot-assisted surgery versus laparoscopic surgery for rectal tumor patients.
Authors: Tajima Jesse Yu , Yokoi Ryoma , Kiyama Shigeru , Hayashi Hirokata , Higashi Toshiya , Asai Ryuichi , Tanaka Yoshihiro , Okumura Naoki , Murase Katsutoshi , Matsuhashi Nobuhisa
Published: August 2023

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Background: Robotic assisted surgery for the rectum has dramatic increased. In addition to the magnifying effect of laparoscopic benefit, robot-assisted surgery has multi-joint function and 3D vision which allows more precise manipulation in the deep pelvic region and is thought to contribute significantly to perioperative safety. However, the superiority of robotic-assisted surgery still remains controversial. In this study, we compared the short-term results of laparoscopic and robotic-assisted surgery for rectal tumors. Methods: This study was a single-center, retrospective study. We included 273 rectal tumor patients who underwent surgery with anastomosis from 2017 to 2021. 169 patients underwent laparoscopic surgery (Lap group) and 104 patients underwent robotic-assisted surgery (Robot group). Postoperative complications were compared by matching using the propensity score based on the IPTW method with the maximum tumor diameter, cT, and cN stage as adjustment factors (SMD≤0.2 was defined as no difference between the groups). Results: Among the patient backgrounds, blood loss, LPLN dissection and tumor diameter showed significant difference. Moreover, rate of cT3-4, cN positive were significantly high in the Lap group. The rate of postoperative complications based on clavien-dindo classification (Lap group vs Robot group), grade II or higher in 29.6% vs 19.2%, grade III or higher in 11.2% vs 5.8% and anastomotic leakage (all grade) in 5.9% vs 4.8%. Adjusted by propensity score matching for all the factors of SMD≤0.2, though there was no significant difference in anastomotic leakage (OR 0.76, 95%CI 0.46-1.27, p=0.296), both postoperative complications of grade II or higher (OR 0.66, 95%CI 0.50-0.87, p=0.004) and grade III or higher (OR 0.29, 95%CI 0.16-0.53, p<0.001) were significantly lower in the Robot group. Conclusions: The results of this study showed better short-term outcomes which suggest that robotic-assisted surgery for rectal tumor is superior in safety than laparoscopic surgery.
Predicting response of gemcitabine plus cisplatin chemotherapy using RNA sequencing in patients with advanced urothelial carcinoma.
Authors: Park Kwonoh , Hong Yun Jeong
Published: August 2023

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Background: Despite of advancement using new agents including ICIs in treatment of urothelial carcinoma (UC), cisplatin-based chemotherapy is still standard of care in both 1st line palliative setting and perioperative setting. Previous studies regarding response prediction of cisplatin-based chemotherapy are limited in selecting target molecule or gene, there have been no comprehensive study for whole genome information. This study aimed to identify key genes to predict response of gemcitabine plus cisplatin (GC) in advanced UC by mRNA sequencing (RNA-seq). Methods: Between JAN 2016 and DEC 2019, advanced UC patients treated with GC and underwent response evaluation were enrolled. Patients were divided into the responder group (CR or PR) and non-responder group (SD or PD). RNA was extracted from the formalin fixed embedded tissue (FFED) and RNA-seq was performed on the Illumina RNA-seq platform. Differentially expressed genes (DEGs) were identified between responder group and non-responder group. Marker selection was performed as following steps: (1) DESeq2 (Adjusted P-value < 0.1) and Mann-Whitney U test (P-value < 0.05), (2) random forest (RF) and logistic regression, and (3) assessments for relevant markers by analyzing RNA/Protein expression level, survival information, and antibody staining results using ProteinAtlas. Results: Twenty-nine patients received GC chemotherapy during study period. Among them, 10 patients who had available FFED specimens and clear response evaluation were enrolled and performed RNA-seq. Median age was 65.5 years (range, 62-76), and all were male. They were grouped of 7 patients in responder and 3 patients in non-responder. Among 13,773 genes based on RNAseq, we identified 37 DEGs candidate (Step 1), followed by 22 DEGs selected (Step 2), and finally 9 DEGs were identified (Step 3). Among the 9 DEGs, 3 genes (UPK2, PCGF3, and POFUT1) were consistently expressed with survival data of TCGA, the expression of 3 (ITGA3, HSPA1B, GSTM3) was the opposite of that of TCGA, and the remaining 3 genes (S100A2, TDRP, and RPS6KA2) were not relevant. Conclusions: We found 3 key genes (UPK2, PCGF3, and POFUT1) that related with favorable response of GC in our advanced UC cohort which were confirmed in TCGA data. Our study results should be further investigated in an expansion cohort using immunohistochemistry staining matched with key genes for convenient practical application.
Effect of low FGFR3 but high CD8 T cell infiltrated immune micro-environment on treatment response with pembrolizumab in upper tract urothelial carcinoma.
Authors: Shigeta Keisuke , Matsumoto Kazuhiro , Yasumizu Yota , Tanaka Nobuyuki , Takeda Toshikazu , Kosaka Takeo , Morita Shinya , Mizuno Ryuichi , Asanuma Hiroshi , Hara Satoshi , Oya Mototsugu
Published: August 2023

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Background: Although several evidence revealed that upper tract urothelial carcinoma (UTUC) with fibroblast growth factor receptor 3 (FGFR3) mutations and/or expressions follow favorable outcomes, the relationship between immune cell markers and FGFR3 expression remains unknown. We aimed to clarify FGFR3 based immune microenvironment and to investigate biomarkers to predict treatment response of Pembrolizumab (Pem) in UTUC patients. Methods: We conducted immunohistochemical (IHC) staining of 214 UTUC patients. FGFR3, CD4, CD8, CD68, CD163, CD204, and PDL-1 expressions were examined and we created immune clusters assessed with heatmap clustering. We assessed the relationships of these immune markers toward further prognosis. In addition, neutrophil-lymphocyte ratio (NLR) and absolute monocyte count (AMC) were evaluated as blodd markers for predicting treatment response from Pem. Results: Among the UTUC patients, 109 (50.9%) showed high FGFR3 expression, and showed favorable prognosis compared to the counterparts. Among the six immune markers, CD8 high expression was revealed as an independent favorable factor (HR=0.44) whereas CD204 high was shown as one of independent prognostic factors for cancer death (HR=1.80). From the FGFFR3 based immune clustering, three immune clusters were identified in UTUC tumor specimen. Cluster A showed FGFR3 low with TAM rich component (CD163 and CD204 high) followed with poor prognosis due to poor response to Pem. Cluster B showed FGFR3 low with immune hot component (CD8 high) followed with most favorable prognosis due to good response to Pembrolizumab. Cluster C showed high FGFR3 expression but immune cold component, followed with favorable prognosis due to FGFR3 high expression but poor response was confirmed with Pem. Regarding of blood biomarkers, NLR showed correlation with CD8 expressions while AMC showed correlation with CD204 expressions. By using validation cohort (n=138), NLR<3.3 showed significantly longer survival compared to the counterparts with Pem treatment (p=0.046). Conclusions: The present study demonstrated a unique immune profile found in UTUC patients. Although most of the patients show poor response to Pem, low FGFR3 expression with immune-hot status may receive clinical benefit from Pem treatment.