Sandip Pravin Patel

Bio: Sandip Pravin Patel is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Medicine & Cancer. The author has an hindex of 30, co-authored 117 publications receiving 5767 citations. Previous affiliations of Sandip Pravin Patel include University of Texas MD Anderson Cancer Center & Duke University.

PD-L1 Expression as a Predictive Biomarker in Cancer Immunotherapy

Abstract: The resurgence of cancer immunotherapy stems from an improved understanding of the tumor microenvironment. The PD-1/PD-L1 axis is of particular interest, in light of promising data demonstrating a restoration of host immunity against tumors, with the prospect of durable remissions. Indeed, remarkable clinical responses have been seen in several different malignancies including, but not limited to, melanoma, lung, kidney, and bladder cancers. Even so, determining which patients derive benefit from PD-1/PD-L1-directed immunotherapy remains an important clinical question, particularly in light of the autoimmune toxicity of these agents. The use of PD-L1 (B7-H1) immunohistochemistry (IHC) as a predictive biomarker is confounded by multiple unresolved issues: variable detection antibodies, differing IHC cutoffs, tissue preparation, processing variability, primary versus metastatic biopsies, oncogenic versus induced PD-L1 expression, and staining of tumor versus immune cells. Emerging data suggest that patients whose tumors overexpress PD-L1 by IHC have improved clinical outcomes with anti-PD-1-directed therapy, but the presence of robust responses in some patients with low levels of expression of these markers complicates the issue of PD-L1 as an exclusionary predictive biomarker. An improved understanding of the host immune system and tumor microenvironment will better elucidate which patients derive benefit from these promising agents.

Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers.

Abstract: Immunotherapy induces durable responses in a subset of patients with cancer. High tumor mutational burden (TMB) may be a response biomarker for PD-1/PD-L1 blockade in tumors such as melanoma and non-small cell lung cancer (NSCLC). Our aim was to examine the relationship between TMB and outcome in diverse cancers treated with various immunotherapies. We reviewed data on 1,638 patients who had undergone comprehensive genomic profiling and had TMB assessment. Immunotherapy-treated patients (N = 151) were analyzed for response rate (RR), progression-free survival (PFS), and overall survival (OS). Higher TMB was independently associated with better outcome parameters (multivariable analysis). The RR for patients with high (≥20 mutations/mb) versus low to intermediate TMB was 22/38 (58%) versus 23/113 (20%; P = 0.0001); median PFS, 12.8 months vs. 3.3 months (P ≤ 0.0001); median OS, not reached versus 16.3 months (P = 0.0036). Results were similar when anti-PD-1/PD-L1 monotherapy was analyzed (N = 102 patients), with a linear correlation between higher TMB and favorable outcome parameters; the median TMB for responders versus nonresponders treated with anti-PD-1/PD-L1 monotherapy was 18.0 versus 5.0 mutations/mb (P < 0.0001). Interestingly, anti-CTLA4/anti-PD-1/PD-L1 combinations versus anti-PD-1/PD-L1 monotherapy was selected as a factor independent of TMB for predicting better RR (77% vs. 21%; P = 0.004) and PFS (P = 0.024). Higher TMB predicts favorable outcome to PD-1/PD-L1 blockade across diverse tumors. Benefit from dual checkpoint blockade did not show a similarly strong dependence on TMB. Mol Cancer Ther; 16(11); 2598-608. ©2017 AACR.

Microbiome analyses of blood and tissues suggest cancer diagnostic approach

Abstract: Systematic characterization of the cancer microbiome provides the opportunity to develop techniques that exploit non-human, microorganism-derived molecules in the diagnosis of a major human disease. Following recent demonstrations that some types of cancer show substantial microbial contributions1–10, we re-examined whole-genome and whole-transcriptome sequencing studies in The Cancer Genome Atlas11 (TCGA) of 33 types of cancer from treatment-naive patients (a total of 18,116 samples) for microbial reads, and found unique microbial signatures in tissue and blood within and between most major types of cancer. These TCGA blood signatures remained predictive when applied to patients with stage Ia–IIc cancer and cancers lacking any genomic alterations currently measured on two commercial-grade cell-free tumour DNA platforms, despite the use of very stringent decontamination analyses that discarded up to 92.3% of total sequence data. In addition, we could discriminate among samples from healthy, cancer-free individuals (n = 69) and those from patients with multiple types of cancer (prostate, lung, and melanoma; 100 samples in total) solely using plasma-derived, cell-free microbial nucleic acids. This potential microbiome-based oncology diagnostic tool warrants further exploration. Microbial nucleic acids are detected in samples of tissues and blood from more than 10,000 patients with cancer, and machine learning is used to show that these can be used to discriminate between and among different types of cancer, suggesting a new microbiome-based diagnostic approach.

Non-small cell lung cancer, version 1.2020: Featured updates to the NCCN guidelines

Abstract: The NCCN Guidelines for Non-Small Cell Lung Cancer (NSCLC) address all aspects of management for NSCLC. These NCCN Guidelines Insights focus on recent updates in immunotherapy. For the 2020 update, all of the systemic therapy regimens have been categorized using a new preference stratification system; certain regimens are now recommended as "preferred interventions," whereas others are categorized as either "other recommended interventions" or "useful under certain circumstances."

NCCN Guidelines Insights: Non–Small Cell Lung Cancer, Version 5.2018

Abstract: The NCCN Guidelines for Non-Small Cell Lung Cancer (NSCLC) address all aspects of management for NSCLC. These NCCN Guidelines Insights focus on recent updates to the targeted therapy and immunotherapy sections in the NCCN Guidelines. For the 2018 update, a new section on biomarkers was added.

Liquid biopsies come of age: towards implementation of circulating tumour DNA

Abstract: Improvements in genomic and molecular methods are expanding the range of potential applications for circulating tumour DNA (ctDNA), both in a research setting and as a 'liquid biopsy' for cancer management. Proof-of-principle studies have demonstrated the translational potential of ctDNA for prognostication, molecular profiling and monitoring. The field is now in an exciting transitional period in which ctDNA analysis is beginning to be applied clinically, although there is still much to learn about the biology of cell-free DNA. This is an opportune time to appraise potential approaches to ctDNA analysis, and to consider their applications in personalized oncology and in cancer research.

PD-L1 Expression as a Predictive Biomarker in Cancer Immunotherapy

Abstract: The resurgence of cancer immunotherapy stems from an improved understanding of the tumor microenvironment. The PD-1/PD-L1 axis is of particular interest, in light of promising data demonstrating a restoration of host immunity against tumors, with the prospect of durable remissions. Indeed, remarkable clinical responses have been seen in several different malignancies including, but not limited to, melanoma, lung, kidney, and bladder cancers. Even so, determining which patients derive benefit from PD-1/PD-L1-directed immunotherapy remains an important clinical question, particularly in light of the autoimmune toxicity of these agents. The use of PD-L1 (B7-H1) immunohistochemistry (IHC) as a predictive biomarker is confounded by multiple unresolved issues: variable detection antibodies, differing IHC cutoffs, tissue preparation, processing variability, primary versus metastatic biopsies, oncogenic versus induced PD-L1 expression, and staining of tumor versus immune cells. Emerging data suggest that patients whose tumors overexpress PD-L1 by IHC have improved clinical outcomes with anti-PD-1-directed therapy, but the presence of robust responses in some patients with low levels of expression of these markers complicates the issue of PD-L1 as an exclusionary predictive biomarker. An improved understanding of the host immune system and tumor microenvironment will better elucidate which patients derive benefit from these promising agents.