Circulating Tumor DNA Assessment for Treatment Monitoring Adds Value to PSA in Metastatic Castration-Resistant Prostate Cancer.

PURPOSE: Enzalutamide after abiraterone progression is commonly used in metastatic castration-resistant prostate cancer despite a low rate of clinical benefit. Analyzing IMbassador250, a phase III trial assessing enzalutamide with or without atezolizumab after abiraterone, we hypothesized that baseline and early changes in circulating tumor DNA (ctDNA) tumor fraction (TF) may identify patients more likely to exhibit survival benefit from enzalutamide. EXPERIMENTAL DESIGN: ctDNA was quantified from plasma samples using a tissue-agnostic assay without buffy coat sequencing. Baseline ctDNA TF, changes in ctDNA TF from baseline to cycle 3 day 1 (C3D1), and detection at C3D1 alone were compared with overall response rate, radiographic progression-free survival (rPFS), median OS (mOS), and 50% reduction in PSA. RESULTS: ctDNA TF detection at baseline and/or C3D1 was associated with shorter rPFS and OS in 494 evaluable patients. Detection of ctDNA TF at C3D1, with or without detection at cycle 1 day 1, was associated with worse rPFS and mOS than lack of detection. When ctDNA TF and PSA response at C3D1 were discordant, patients with (ctDNA TF undetected/PSA not reduced) had more favorable outcomes than (ctDNA TF detected/PSA reduced; mOS 22.1 vs. 16 months; P < 0.001). CONCLUSIONS: In a large cohort of patients with metastatic castration-resistant prostate cancer receiving enzalutamide after abiraterone, we demonstrate the utility of a new tissue-agnostic assay for monitoring molecular response based on ctDNA TF detection and dynamics. ctDNA TF provides a minimally invasive, complementary biomarker to PSA testing and may refine personalized treatment approaches.

Analytical validation of a novel comprehensive genomic profiling informed circulating tumor DNA monitoring assay for solid tumors.

Emerging technologies focused on the detection and quantification of circulating tumor DNA (ctDNA) in blood show extensive potential for managing patient treatment decisions, informing risk of recurrence, and predicting response to therapy. Currently available tissue-informed approaches are often limited by the need for additional sequencing of normal tissue or peripheral mononuclear cells to identify non-tumor-derived alterations while tissue-naïve approaches are often limited in sensitivity. Here we present the analytical validation for a novel ctDNA monitoring assay, FoundationOne®Tracker. The assay utilizes somatic alterations from comprehensive genomic profiling (CGP) of tumor tissue. A novel algorithm identifies monitorable alterations with a high probability of being somatic and computationally filters non-tumor-derived alterations such as germline or clonal hematopoiesis variants without the need for sequencing of additional samples. Monitorable alterations identified from tissue CGP are then quantified in blood using a multiplex polymerase chain reaction assay based on the validated SignateraTM assay. The analytical specificity of the plasma workflow is shown to be 99.6% at the sample level. Analytical sensitivity is shown to be >97.3% at ≥5 mean tumor molecules per mL of plasma (MTM/mL) when tested with the most conservative configuration using only two monitorable alterations. The assay also demonstrates high analytical accuracy when compared to liquid biopsy-based CGP as well as high qualitative (measured 100% PPA) and quantitative precision (<11.2% coefficient of variation).

Tumor sequencing of African ancestry reveals differences in clinically relevant alterations across common cancers.

Cancer genomes from patients with African (AFR) ancestry have been poorly studied in clinical research. We leverage two large genomic cohorts to investigate the relationship between genomic alterations and AFR ancestry in six common cancers. Cross-cancer type associations, such as an enrichment of MYC amplification with AFR ancestry in lung, breast, and prostate cancers, and depletion of BRAF alterations are observed in colorectal and pancreatic cancers. There are differences in actionable alterations, such as depletion of KRAS G12C and EGFR L858R, and enrichment of ROS1 fusion with AFR ancestry in lung cancers. Interestingly, in lung cancer, KRAS mutations are less common in both smokers and non-smokers with AFR ancestry, whereas the association of TP53 mutations with AFR ancestry is only seen in smokers, suggesting an ancestry-environment interaction that modifies driver rates. Our study highlights the need to increase representation of patients with AFR ancestry in drug development and biomarker discovery.

Pan-Cancer Analysis of Copy-Number Features Identifies Recurrent Signatures and a Homologous Recombination Deficiency Biomarker to Predict Poly (ADP-Ribose) Polymerase Inhibitor Response.

PURPOSE: Copy-number (CN) features reveal the molecular state of cancers and may have predictive and prognostic value in the treatment of cancer. We sought to apply published CN analysis methods to a large pan-cancer data set and characterize ubiquitous CN signatures across tumor types, including potential utility for treatment selection. METHODS: We analyzed the landscape of CN features in 260,333 pan-cancer samples. We examined the association of 10 signatures with genomic alterations and clinical characteristics and trained a machine learning classifier using CN and insertion and deletion features to detect homologous recombination deficiency signature (HRDsig) positivity. Clinical outcomes were assessed using a real-world clinicogenomic database (CGDB) of comprehensive genomic profiling linked to deidentified, electronic health record-derived clinical data. RESULTS: CN signatures were prevalent across cancer types and associated with diverse processes including focal tandem duplications, seismic amplifications, genome-wide loss of heterozygosity (gLOH), and HRD. Our novel HRDsig outperformed gLOH in predicting BRCAness and effectively distinguished biallelic BRCA and homologous recombination-repair wild-type (HRRwt) samples pan-tumor, demonstrating high sensitivity to detect biallelic BRCA in ovarian (93%) and other HRD-associated cancers (80%-87%). Pan-tumor prevalence of HRDsig was 6.4%. HRRwt cases represented a significant fraction of the HRDsig-positive cohort, likely reflecting a population with nongenomic mechanisms of HRD. In ovarian and prostate CGDBs, HRDsig identified more patients than gLOH and had predictive value for poly (ADP-ribose) polymerase inhibitor (PARPi) benefit. CONCLUSION: Tumor CN profiles are informative, revealing diverse processes active in cancer. We describe the landscape of 10 CN signatures in a large pan-cancer cohort, including two associated with HRD. We trained a machine learning-based HRDsig that robustly identified BRCAness and associated with biallelic BRCA pan-tumor, and was predictive of PARPi benefit in real-world ovarian and prostate data sets.

Molecular residual disease detection in resected, muscle-invasive urothelial cancer with a tissue-based comprehensive genomic profiling-informed personalized monitoring assay.

Introduction: Circulating tumor DNA (ctDNA) detection postoperatively may identify patients with urothelial cancer at a high risk of relapse. Pragmatic tools building off clinical tumor next-generation sequencing (NGS) platforms could have the potential to increase assay accessibility. Methods: We evaluated the widely available Foundation Medicine comprehensive genomic profiling (CGP) platform as a source of variants for tracking of ctDNA when analyzing residual samples from IMvigor010 (ClinicalTrials.gov identifier NCT02450331), a randomized adjuvant study comparing atezolizumab with observation after bladder cancer surgery. Current methods often involve germline sampling, which is not always feasible or practical. Rather than performing white blood cell sequencing to filter germline and clonal hematopoiesis (CH) variants, we applied a bioinformatic approach to select tumor (non-germline/CH) variants for molecular residual disease detection. Tissue-informed personalized multiplex polymerase chain reaction-NGS assay was used to detect ctDNA postsurgically (Natera). Results: Across 396 analyzed patients, prevalence of potentially actionable alterations was comparable with the expected prevalence in advanced disease (13% FGFR2/3, 20% PIK3CA, 13% ERBB2, and 37% with elevated tumor mutational burden ≥10 mutations/megabase). In the observation arm, 66 of the 184 (36%) ctDNA-positive patients had shorter disease-free survival [DFS; hazard ratio (HR) = 5.77; 95% confidence interval (CI), 3.84-8.67; P < 0.0001] and overall survival (OS; HR = 5.81; 95% CI, 3.41-9.91; P < 0.0001) compared with ctDNA-negative patients. ctDNA-positive patients had improved DFS and OS with atezolizumab compared with those in observation (DFS HR = 0.56; 95% CI, 0.38-0.83; P = 0.003; OS HR = 0.66; 95% CI, 0.42-1.05). Clinical sensitivity and specificity for detection of postsurgical recurrence were 58% (60/103) and 93% (75/81), respectively. Conclusion: We present a personalized ctDNA monitoring assay utilizing tissue-based FoundationOne® CDx CGP, which is a pragmatic and potentially clinically scalable method that can detect low levels of residual ctDNA in patients with resected, muscle-invasive bladder cancer without germline sampling.

A Novel HRD Signature Is Predictive of FOLFIRINOX Benefit in Metastatic Pancreatic Cancer.

BACKGROUND: Pancreatic cancer (PC) represents an aggressive disease with median overall survival (OS) of less than 1 year in the front-line setting. FOLFIRINOX and gemcitabine and paclitaxel (GP) are standard of care options for these patients; however, optimal selection of therapy is challenging. METHODS: Comprehensive genomic profiling was performed on 8358 PC patients. Outcomes were available for 1149 metastatic PC patients treated with 1L FOLFIRINOX or GP. A scar-based measure of HRD was called using a machine learning-based algorithm incorporating copy number and indel features. RESULTS: A scar-based HRD signature (HRDsig) was identified in 9% of patients. HRDsig significantly co-occurred with biallelic alterations in BRCA1/2, PALB2, BARD1, and RAD51C/D, but encompassed a larger population than that defined by BRCA1/BRCA2/PALB2 (9% vs. 6%). HRDsig was predictive of 1L FOLFIRNOX chemotherapy benefit with doubled OS relative to gemcitabine and paclitaxel (GP) (rwOS aHR 0.37 [0.22-0.62]), including 25% of the population with long-term (2 year+) survival in a real-world cohort of patients. Less benefit from FOLFIRINOX was observed in the HRDsig(-) population. Predictive value was seen in both the BRCA1/2/PALB2 mutant and wildtype populations, suggesting additional value to mutational profiling. CONCLUSION: A scar-based HRD biomarker was identified in a significant fraction of PC patients and is predictive of FOLFIRINOX benefit. Incorporating a biomarker like HRDsig could identify the right patients for platinum chemotherapy and potentially reduce FOLFIRINOX use by over 40%, minimizing toxicities with similar survival outcomes. Confirmatory studies should be performed.

Integrative Analysis of a Large Real-World Cohort of Small Cell Lung Cancer Identifies Distinct Genetic Subtypes and Insights into Histologic Transformation.

Small cell lung cancer (SCLC) is a recalcitrant neuroendocrine carcinoma with dismal survival outcomes. A major barrier in the field has been the relative paucity of human tumors studied. Here we provide an integrated analysis of 3,600 "real-world" SCLC cases. This large cohort allowed us to identify new recurrent alterations and genetic subtypes, including STK11-mutant tumors (1.7%) and TP53/RB1 wild-type tumors (5.5%), as well as rare cases that were human papillomavirus-positive. In our cohort, gene amplifications on 4q12 are associated with increased overall survival, whereas CCNE1 amplification is associated with decreased overall survival. We also identify more frequent alterations in the PTEN pathway in brain metastases. Finally, profiling cases of SCLC containing oncogenic drivers typically associated with NSCLC demonstrates that SCLC transformation may occur across multiple distinct molecular cohorts of NSCLC. These novel and unsuspected genetic features of SCLC may help personalize treatment approaches for this fatal form of cancer. SIGNIFICANCE: Minimal changes in therapy and survival outcomes have occurred in SCLC for the past four decades. The identification of new genetic subtypes and novel recurrent mutations as well as an improved understanding of the mechanisms of transformation to SCLC from NSCLC may guide the development of personalized therapies for subsets of patients with SCLC. This article is highlighted in the In This Issue feature, p. 1501.

Predicting EGFR mutational status from pathology images using a real-world dataset.

Treatment of non-small cell lung cancer is increasingly biomarker driven with multiple genomic alterations, including those in the epidermal growth factor receptor (EGFR) gene, that benefit from targeted therapies. We developed a set of algorithms to assess EGFR status and morphology using a real-world advanced lung adenocarcinoma cohort of 2099 patients with hematoxylin and eosin (H&E) images exhibiting high morphological diversity and low tumor content relative to public datasets. The best performing EGFR algorithm was attention-based and achieved an area under the curve (AUC) of 0.870, a negative predictive value (NPV) of 0.954 and a positive predictive value (PPV) of 0.410 in a validation cohort reflecting the 15% prevalence of EGFR mutations in lung adenocarcinoma. The attention model outperformed a heuristic-based model focused exclusively on tumor regions, and we show that although the attention model also extracts signal primarily from tumor morphology, it extracts additional signal from non-tumor tissue regions. Further analysis of high-attention regions by pathologists showed associations of predicted EGFR negativity with solid growth patterns and higher peritumoral immune presence. This algorithm highlights the potential of deep learning tools to provide instantaneous rule-out screening for biomarker alterations and may help prioritize the use of scarce tissue for biomarker testing.

CD8+ T cell-intrinsic IL-6 signaling promotes resistance to anti-PD-L1 immunotherapy.

Although immune checkpoint inhibitors (ICIs) are established as effective cancer therapies, overcoming therapeutic resistance remains a critical challenge. Here we identify interleukin 6 (IL-6) as a correlate of poor response to atezolizumab (anti-PD-L1) in large clinical trials of advanced kidney, breast, and bladder cancers. In pre-clinical models, combined blockade of PD-L1 and the IL-6 receptor (IL6R) causes synergistic regression of large established tumors and substantially improves anti-tumor CD8+ cytotoxic T lymphocyte (CTL) responses compared with anti-PD-L1 alone. Circulating CTLs from cancer patients with high plasma IL-6 display a repressed functional profile based on single-cell RNA sequencing, and IL-6-STAT3 signaling inhibits classical cytotoxic differentiation of CTLs in vitro. In tumor-bearing mice, CTL-specific IL6R deficiency is sufficient to improve anti-PD-L1 activity. Thus, based on both clinical and experimental evidence, agents targeting IL-6 signaling are plausible partners for combination with ICIs in cancer patients.

Genomic Profiling Reveals Differences in Primary Central Nervous System Lymphoma and Large B-Cell Lymphoma, With Subtyping Suggesting Sensitivity to BTK Inhibition.

BACKGROUND: B-cell primary central nervous system (CNS) lymphoma (PCL) is diffuse large B-cell lymphoma (DLBCL) confined to the CNS. Less than 50% of patients with PCL achieve complete remission with current therapies. We describe the findings from comprehensive genomic profiling (CGP) of a cohort of 69 patients with PCL, 36 cases of secondary CNS lymphoma (SCL), and 969 cases of DLBCL to highlight their differences and characterize the PCL cohort. In addition, we highlight the differences in frequency of germinal center B-cell like (GCB) and non-GCB subtypes and molecular subtypes, particularly MCD and EZH subtypes, between PCL and DLBCL. MATERIALS AND METHODS: Sixty-nine cases of B-cell PCL, 36 cases of secondary CNS lymphoma (SCL), and 969 cases of DLBCL were evaluated by CGP of 405 genes via DNAseq and 265 genes via RNAseq for fusions (FoundationOne Heme). Tumor mutational burden (TMB) was calculated from 1.23 Mb of sequenced DNA. RESULTS: Genomic alterations with significant differences between PCL and DLBCL included MYD88, ETV6, PIM1, PRDM1, CXCR4, TP53, and CREBBP, while only MYD88 was significantly different between SCL and DLBCL. PCL cases were significantly enriched for the MCD molecular subtypes, which have an excellent response to BTKi. We report a patient with a durable complete response to BTKi consistent with their genomic profile. EBV status, CD274 amplification, and TMB status suggest that 38% of PCL patients may benefit from ICPI; however further study is warranted. CONCLUSION: CGP of PCLs reveals biomarkers, genomic alterations, and molecular classifications predictive of BTKi efficacy and potential ICPI efficacy. Given the limitations of standard of care for PCL, CGP is critical to identify potential therapeutic approaches for patients in this rare form of lymphoma.

Tissue and liquid biopsy profiling reveal convergent tumor evolution and therapy evasion in breast cancer.

Pathological and genomic profiling have transformed breast cancer care by matching patients to targeted treatments. However, tumors evolve and evade therapeutic interventions often through the acquisition of genomic mutations. Here we examine patients profiled with tissue (TBx) and liquid biopsy (LBx) as part of routine clinical care, to characterize the tumor evolutionary landscape and identify potential vulnerabilities in the relapsed setting. Real-world evidence demonstrates that LBx is utilized later in care and identifies associations with intervening therapy. While driver events are frequently shared, acquired LBx alterations are detected in a majority of patients, with the highest frequency in ER+ disease and in patients with longer biopsy intervals. Acquired mutations are often polyclonal and present at lower allelic fractions, suggesting multi-clonal convergent evolution. In addition to well-characterized resistance mutations (e.g., ESR1, NF1, RB1, ERBB2), we observe a diversity of rarer but potentially targetable mutations (e.g., PIK3CA, HRAS/NRAS/KRAS, FGFR1/2/3, BRAF) and fusions (e.g., FGFR1/2, ERBB2, RET), as well as BRCA1/2 reversions through a variety of mechanisms, including splice alterations and structural deletions. This study provides insights on treatment and selection-driven tumor evolution and identifies potential combinatorial treatment options in advanced breast cancer.

Comprehensive pan-cancer genomic landscape of KRAS altered cancers and real-world outcomes in solid tumors.

Recent clinical development of KRAS inhibitors has heightened interest in the genomic landscape of KRAS-altered cancers. We performed a pan-cancer analysis of KRAS-altered samples from 426,706 adult patients with solid or hematologic malignancies using comprehensive genomic profiling; additional analyses included 62,369 liquid biopsy and 7241 pediatric samples. 23% of adult pan-cancer samples had KRAS alterations; 88% were mutations, most commonly G12D/G12V/G12C/G13D/G12R, and prevalence was similar in liquid biopsies. Co-alteration landscapes were largely similar across KRAS mutations but distinct from KRAS wild-type, though differences were observed in some tumor types for tumor mutational burden, PD-L1 expression, microsatellite instability, and other mutational signatures. Prognosis of KRAS-mutant versus other genomic cohorts of lung, pancreatic, and colorectal cancer were assessed using a real-world clinicogenomic database. As specific KRAS inhibitors and combination therapeutic strategies are being developed, genomic profiling to understand co-alterations and other biomarkers that may modulate response to targeted or immunotherapies will be imperative.

Comprehensive Genomic Profiling (CGP)-Informed Personalized Molecular Residual Disease (MRD) Detection: An Exploratory Analysis from the PREDATOR Study of Metastatic Colorectal Cancer (mCRC) Patients Undergoing Surgical Resection.

A majority of patients with metastatic colorectal cancer (mCRC) experience recurrence post curative-intent surgery. The addition of adjuvant chemotherapy has shown to provide limited survival benefits when applied to all patients. Therefore, a biomarker to assess molecular residual disease (MRD) accurately and guide treatment selection is highly desirable for high-risk patients. This feasibility study evaluated the prognostic value of a tissue comprehensive genomic profiling (CGP)-informed, personalized circulating tumor DNA (ctDNA) assay (FoundationOne®Tracker) (Foundation Medicine, Inc., Cambridge, MA, USA) by correlating MRD status with clinical outcomes. ctDNA analysis was performed retrospectively on plasma samples from 69 patients with resected mCRC obtained at the MRD and the follow-up time point. Tissue CGP identified potentially actionable alterations in 54% (37/69) of patients. MRD-positivity was significantly associated with lower disease-free survival (DFS) (HR: 4.97, 95% CI: 2.67−9.24, p < 0.0001) and overall survival (OS) (HR: 27.05, 95% CI: 3.60−203.46, p < 0.0001). Similarly, ctDNA positive status at the follow-up time point correlated with a marked reduction in DFS (HR: 8.78, 95% CI: 3.59−21.49, p < 0.0001) and OS (HR: 20.06, 95% CI: 2.51−160.25, p < 0.0001). The overall sensitivity and specificity at the follow-up time point were 69% and 100%, respectively. Our results indicate that MRD detection using the tissue CGP-informed ctDNA assay is prognostic of survival outcomes in patients with resected mCRC. The concurrent MRD detection and identification of actionable alterations has the potential to guide perioperative clinical decision-making.

Case report: A persistently expanded T cell response in an exceptional responder to radiation and atezolizumab for metastatic non-small cell lung cancer.

Most patients with advanced non-small cell lung cancer (NSCLC) do not achieve a durable remission after treatment with immune checkpoint inhibitors. Here we report the clinical history of an exceptional responder to radiation and anti-program death-ligand 1 (PD-L1) monoclonal antibody, atezolizumab, for metastatic NSCLC who remains in a complete remission more than 8 years after treatment. Sequencing of the patient's T cell repertoire from a metastatic lesion and the blood before and after anti-PD-L1 treatment revealed oligoclonal T cell expansion. Characterization of the dominant T cell clone, which comprised 10% of all clones and increased 10-fold in the blood post-treatment, revealed an activated CD8+ phenotype and reactivity against 4 HLA-A2 restricted neopeptides but not viral or wild-type human peptides, suggesting tumor reactivity. We hypothesize that the patient's exceptional response to anti-PD-L1 therapy may have been achieved by increased tumor immunogenicity promoted by pre-treatment radiation therapy as well as long-term persistence of oligoclonal expanded circulating T cells.

Association of CD274 (PD-L1) Copy Number Changes with Immune Checkpoint Inhibitor Clinical Benefit in Non-Squamous Non-Small Cell Lung Cancer.

BACKGROUND: We sought to characterize response to immune checkpoint inhibitor (ICI) in non-squamous non-small cell lung cancer (NSCLC) across various CD274 copy number gain and loss thresholds and identify an optimal cutoff. MATERIALS AND METHODS: A de-identified nationwide (US) real-world clinico-genomic database was leveraged to study 621 non-squamous NSCLC patients treated with ICI. All patients received second-line ICI monotherapy and underwent comprehensive genomic profiling as part of routine clinical care. Overall survival (OS) from start of ICI, for CD274 copy number gain and loss cohorts across varying copy number thresholds, were assessed. RESULTS: Among the 621 patients, patients with a CD274 CN greater than or equal to specimen ploidy +2 (N = 29) had a significantly higher median (m) OS when compared with the rest of the cohort (N = 592; 16.1 [8.9-37.3] vs 8.6 [7.1-10.9] months, hazard ratio (HR) = 0.6 [0.4-1.0], P-value = .05). Patients with a CD274 copy number less than specimen ploidy (N = 299) trended toward a lower mOS when compared to the rest of the cohort (N = 322; 7.5 [5.9-11.3] vs 9.6 [7.9-12.8] months, HR = 0.9 [0.7-1.1], P-value = .3). CONCLUSION: This work shows that CD274 copy number gains at varying thresholds predict different response to ICI blockade in non-squamous NSCLC. Considering these data, prospective clinical trials should further validate these findings, specifically in the context of PD-L1 IHC test results.

Driver Mutation Variant Allele Frequency in Circulating Tumor DNA and Association with Clinical Outcome in Patients with Non-Small Cell Lung Cancer and EGFR- and KRAS-Mutated Tumors.

Clinical implementation of mutational analysis for next-generation sequencing-based assays has largely been of a binary nature, with pathogenic mutations being reported as either positive or negative. Actionability on the continuous output of variant allele frequency (VAF) has not been well characterized in the clinical setting, thus limiting its use. In this study, analytical validity and performance of the short variant VAF based on a next-generation sequencing-based liquid biopsy assay, FoundationOne Liquid CDx, were evaluated through assessment of precision, analytical accuracy, limit of blank, and limit of detection. Analytical validation of VAF values measured by using FoundationOne Liquid CDx supports that these values are accurate, precise, robust, and linear with the true VAF value. The association of allele frequency of clinically relevant short variants in circulating-free DNA and the association with overall survival for patients using real-world data were also assessed. The results of the association analysis indicate that VAF of the predictive biomarker mutation negatively correlates with overall survival of patients with non-small cell lung cancer.

Transcriptomic profiling of adjuvant colorectal cancer identifies three key prognostic biological processes and a disease specific role for granzyme B.

BACKGROUND: Colorectal cancer (CRC) is a leading cause of cancer-related deaths, with a 5% 5-year survival rate for metastatic disease, yet with limited therapeutic advancements due to insufficient understanding of and inability to accurately capture high-risk CRC patients who are most likely to recur. We aimed to improve high-risk classification by identifying biological pathways associated with outcome in adjuvant stage II/III CRC. METHODS AND FINDINGS: We included 1062 patients with stage III or high-risk stage II colon carcinoma from the prospective three-arm randomized phase 3 AVANT trial, and performed expression profiling to identify a prognostic signature. Data from validation cohort GSE39582, The Cancer Genome Atlas, and cell lines were used to further validate the prognostic biology. Our retrospective analysis of the adjuvant AVANT trial uncovered a prognostic signature capturing three biological functions-stromal, proliferative and immune-that outperformed the Consensus Molecular Subtypes (CMS) and recurrence prediction signatures like Oncotype Dx in an independent cohort. Importantly, within the immune component, high granzyme B (GZMB) expression had a significant prognostic impact while other individual T-effector genes were less or not prognostic. In addition, we found GZMB to be endogenously expressed in CMS2 tumor cells and to be prognostic in a T cell independent fashion. A limitation of our study is that these results, although robust and derived from a large dataset, still need to be clinically validated in a prospective study. CONCLUSIONS: This work furthers our understanding of the underlying biology that propagates stage II/III CRC disease progression and provides scientific rationale for future high-risk stratification and targeted treatment evaluation in biomarker defined subpopulations of resectable high-risk CRC. Our results also shed light on an alternative GZMB source with context-specific implications on the disease's unique biology.

Molecular determinants of response to PD-L1 blockade across tumor types.

Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity is observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC are molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A is identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis reveals molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.

Intratumoral CD103+ CD8+ T cells predict response to PD-L1 blockade.

BACKGROUND: CD8+ tissue-resident memory T (TRM) cells, marked by CD103 (ITGAE) expression, are thought to actively suppress cancer progression, leading to the hypothesis that their presence in tumors may predict response to immunotherapy. METHODS: Here, we test this by combining high-dimensional single-cell modalities with bulk tumor transcriptomics from 1868 patients enrolled in lung and bladder cancer clinical trials of atezolizumab (anti-programmed cell death ligand 1 (PD-L1)). RESULTS: ITGAE was identified as the most significantly upregulated gene in inflamed tumors. Tumor CD103+ CD8+ TRM cells exhibited a complex phenotype defined by the expression of checkpoint regulators, cytotoxic proteins, and increased clonal expansion. CONCLUSIONS: Our analyses indeed demonstrate that the presence of CD103+ CD8+ TRM cells, quantified by tracking intratumoral CD103 expression, can predict treatment outcome, suggesting that patients who respond to PD-1/PD-L1 blockade are those who exhibit an ongoing antitumor T-cell response.