Liquid Biopsies and IMAging for Improved Cancer Care

Study Overview
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Brief Summary
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The recently developed liquid biopsy technology (to obtain and characterize tumour cells and tumour components like Deoxyribonucleic acid (DNA) or Ribonucleic Acid (RNA) from a simple blood draw), in combination with advanced Magnetic Resonance Imaging techniques (MRI), can tackle the following problems in rectal cancer: 1. Assessment of tumour heterogeneity from liquid biopsies. 2. Assessment from advanced MRI feature extraction to indicate poor outcome 3. Faster assessment of therapy response in Neoadjuvant chemotherapy (NAT) for rectal cancer; 4. Detection of emerging drug/therapy resistance. This project's overall objective is to develop and validate technologies and tools to include liquid biopsies in the clinical workflow, aiming at introducing a more precise and dynamic genetic characterization of tumour at the diagnosis and during treatment phases.

Detailed Description
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According to the Global cancer observatory database (Globocan) estimates, there are 447,136 new cases of Colo-Rectal Cancer (CRC) in Europe annually. This makes CRC the 2nd most common cancer in Europe, accounting for 13.0% of all cancers in 2012 with an estimate of 214,866 deaths from CRC in Europe (12.2% of the total number of cancer deaths, 2nd most common cause of cancer related deaths). In LIMA, the rectal cancer patient sub-group of CRC will be studied, comprising some 80,000 patients annually, as these patients are treated in neoadjuvant setting. Moreover, ineffective NeoAdjuvant Treatment (NAT) in rectal cancer patients will results in surgery with severe side effect, making stratification of patients according to their Neoadjuvant Chemotherapy (NAT) response a real challenge for this pathology. Cancer is a very heterogeneous disease characterized by high variability of response to therapy. In general, it is unknown which cancers will respond to a certain therapy and which will not. Overall trend is to come to less invasive and more personalized treatment. Personalized medicine for cancer patients aims to tailor the best treatment options for the individual at diagnosis and during treatment. This requires accurate patient stratification based on molecular profiling of the tumour and its heterogeneity, not only at the first diagnosis but during the whole treatment. Treatment of cancer is associated with significant comorbidity and reduced quality of life, especially when an organ like the rectum, would need to be surgically removed to increase chances of curation of the disease. But also side-effects of treatment are important to consider. In the past decade the use of NAT has emerged as an effective therapeutic approach to reduce tumour volume and aggressiveness prior to surgery, resulting in increased chances at curative resection and saving the organ and to test sensitivity of a tumour to a therapy that will be used in adjuvant setting following surgery. The development of drugs that target tumour driving signal transduction pathways provides a very effective set of new cancer drugs to choose from in the neoadjuvant or adjuvant setting. This is based however on the premise that the tumour driving pathway is accurately defined in the tumour tissue and the appropriate targeted drug is selected. Using these drugs requires a personalized approach with careful matching of patient to drug therapy. In the neoadjuvant setting this poses a challenge, since tumours can be heterogenic with respect to the tumour driving signalling pathways, especially when high grade and larger sized. In such a case, multiple biopsies would need to be taken to enable accurate characterization of the whole tumour. Unfortunately this is often not feasible, while recent insights suggest that resulting inflammation of the tumour microenvironment may contribute to a more aggressive behaviour of the cancer cells. Another challenge in neoadjuvant treatment is early assessment of therapy response, to enable timely switching to another, more effective therapy in case of a non-response. In addition, in the case of use of targeted drugs, emerging resistance can be a problem, which should be detected as soon as possible. Aim of this project is to improve monitoring of patients' response at the diagnosis and during neoadjuvant treatment, to stratify the good and poor responders to Neoadjuvant chemotherapy (NAT), earlier and better than is currently possible. The recently developed liquid biopsy technology (to obtain and characterize tumour cells and tumour components like Deoxyribonucleic Acid (DNA) or Ribonucleic Acid (RNA) from a simple blood draw), in combination with advanced Magnetic Resonance Imaging techniques (MRI), can tackle the following problems: 1. Assessment of tumour heterogeneity from liquid biopsies. 2. Assessment from advanced MRI feature extraction to indicate poor outcome 3. Faster assessment of therapy response in NAT for rectal cancer; 4. Detection of emerging drug/therapy resistance. This project overall objective is to develop and validate technologies and tools to include liquid biopsies in the clinical workflow, aiming at introducing a more precise and dynamic genetic characterization of tumour at the diagnosis and during treatment phases.

Official Title
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Liquid Biopsies and IMAging for Improved Cancer Care - Non Metastatic Rectal Cancer

Conditions
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Rectal Cancer

Intervention / Treatment
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* Biological: Biological collection


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Age ≥ 18 years old Histologically-confirmed diagnosis of adenocarcinoma of the rectum Distal part of the tumour within 2 to 12 cm of the anal margin Candidate for Neoadjuvant chemotherapy (NAT) Measurable disease (using the Recist criteria v1.1) Eastern Cooperative Oncology Group (ECOG) performance status 0-1 General condition considered suitable for radical pelvic surgery Adequate bone marrow, hepatic and renal function Willing to participate to the study, and able to give informed consent and to comply with the treatment and follow-up schedules Patient being able to follow all the treatment as well as the follow-ups planned in this study Exclusion Criteria: Patient with metastatic disease Symptomatic cardiac or coronary insufficiency Severe renal insufficiency Progressive active infection or any other severe medical condition Other cancer treated within the last 5 years except in situ cervical carcinoma or basocellular/ spinocellular carcinoma Pregnant or breast-feeding woman Unaffiliated patient to French Social Protection System Persons deprived of liberty or under guardianship or incapable of giving consent Any psychological, familial, sociological or geographical condition potentially hampering compliance with the study protocol or follow-up schedule

Ages Eligible for Study
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Minimum Age: 18 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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No

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Diagnostic
Intervention Model: Single Group Assignment
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: Tumors and blood collection<br>For all the patients included in the study : Blood samples will be collected at different times T1 (Baseline), T2 (1 or 2 weeks after the beginning of the treatment), T3 (3 or 4 weeks before the surgery) and T4 (1 month after the surgery). Tumors biopsy will be collected for some patients who will benefit from an initial biopsy in the course of his management care in our Institute (before the surgery). In parallel to this biological collection, imaging and clinical data will be entered into a database treatment. | Biological: Biological collection<br>* The biological collection will include samples of blood samples collected at different times but also tumoral biopsy before the surgery.<br>|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Area under the Receiver Operating Characteristic (ROC) curve of total cfDNA (defined as circulating cell-free DNA in plasma) percent change between the baseline sample (T1) and the sample at the end of the neo-adjuvant treatment (T3) | This change of circulating free DeoxyriboNucleic Acid (cfDNA) percent will be correlated with the pathological complete response (defined as Grade 3 and 4 of Dworak definition) to neo-adjuvant treatment Pathological response (at surgery) is defined as Dworak definition below: No regression (0), Predominantly tumour with significant fibrosis and/or vasculopathy (1), Predominantly fibrosis with scattered tumour cells (slightly recognizable histologically) (2), Only scattered tumour cells in the space of fibrosis with / without acellular mucin (3) No vital tumour cells detectable (4). | Through study completion, an average of 3.5 years | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Area under the Receiver Operating Characteristic (ROC) curve of the total cfDNA percent change between the baseline sample (T1) and the first sample during the neo-adjuvant treatment (T2) | This change of circulating free DeoxyriboNucleic Acid (cfDNA) percent will be correlated with the pathological complete response | Through study completion, an average of 3.5 years | 
| Area under the Receiver Operating Characteristic (ROC) curve of the mutant cfDNA percent change between the baseline sample (T1) and the first sample during the neo-adjuvant treatment (T2) [resp the sample at the end of neo-adjuvant treatment (T3)] | This change of circulating free DeoxyriboNucleic Acid (cfDNA) percent will be correlated with the pathological complete response | Through study completion, an average of 3.5 years | 
| Number of Circulating tumor cells (CTCs) found in blood |  | Through study completion, an average of 3.5 years | 
| Tumoral response assessed by Magnetic resonance Imaging (MRI) | Tumor evaluation will be evaluated according to DISTANCE parameters | Through study completion, an average of 3.5 years | 
| Response to treatment by using a radiomics algorythm | The term radiomics has been defined as high-throughput extraction of quantitative features that results in the conversion of images into mineable data | Through study completion, an average of 3.5 years | 
| Sensibility (Se) of the total cfDNA percent change and the mutant cfDNA percent change | Between the baseline (sample T1) and the first sample during the neo-adjuvant treatment (T2) [respectively the sample at the end of neo-adjuvant treatment (T3)] and the complete pathological response to neo-adjuvant treatment Mutant cftDNA is defined as cfDNA bearing the mutations detected from RAS, BRAF and PIK3CA | Through study completion, an average of 3.5 years | 
| Specificity (Se) of the total cfDNA percent change and the mutant cfDNA percent change | Between the baseline (sample T1) and the first sample during the neo-adjuvant treatment (T2) [respectively the sample at the end of neo-adjuvant treatment (T3)] and the complete pathological response to neo-adjuvant treatment Mutant cftDNA is defined as cfDNA bearing the mutations detected from RAS, BRAF and PIK3CA | Through study completion, an average of 3.5 years | 
| Predictive Positive Value (PPV) of the total cfDNA percent change and the mutant cfDNA percent change | Between the baseline (sample T1) and the first sample during the neo-adjuvant treatment (T2) [respectively the sample at the end of neo-adjuvant treatment (T3)] and the complete pathological response to neo-adjuvant treatment. Mutant cftDNA is defined as cfDNA bearing the mutations detected from RAS, BRAF and PIK3CA | Through study completion, an average of 3.5 years | 
| Predictive Negative Value (PNV) of the total cfDNA percent change and the mutant cfDNA percent change | Between the baseline (sample T1) and the first sample during the neo-adjuvant treatment (T2) [respectively the sample at the end of neo-adjuvant treatment (T3)] and the complete pathological response to neo-adjuvant treatment Mutant cftDNA is defined as cfDNA bearing the mutations detected from RAS, BRAF and PIK3CA | Through study completion, an average of 3.5 years | 
| The number of molecular signal transduction pathway that appear in addition to the wingless integration site (Wnt) pathway at T1, T2, T3 and T4 |  | Through study completion, an average of 3.5 years | 
| Tumoral response assessed by Magnetic resonance Imaging (MRI) | Tumor volumetry will be performed manually, tracing the tumor boundaries on the axial oblique images on T2W-MR images in conjunction with the highest b value image as to exclude areas of T2 fibrosis and include only the residual tumor | Through study completion, an average of 3.5 years | 
| Tumoral response assessed by Magnetic resonance Imaging (MRI) | The mrTRG will be also evaluated to determine the degree of tumor replacement by fibrotic or mucinous changes stroma. Favorable mrTRG will be defined as grades 1 and 2, and unfavorable mrTRG as stages 3, 4 and 5 | Through study completion, an average of 3.5 years |