Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy.

Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. We developed approaches to categorize solid tumors into 'desert', 'excluded', and 'inflamed' types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach, we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. We show that categorization based on 'manual' observation is predictive for clinical benefit from anti-programmed death ligand 1 therapy in two large cohorts of patients with non-small cell lung cancer or triple-negative breast cancer. For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based readouts and the patient's response to therapy. Our findings suggest that tumor immunophenotype generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. © 2024 The Pathological Society of Great Britain and Ireland.

Image-based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno-oncology Biomarker Working Group on Breast Cancer.

Recent advances in the field of immuno-oncology have brought transformative changes in the management of cancer patients. The immune profile of tumours has been found to have key value in predicting disease prognosis and treatment response in various cancers. Multiplex immunohistochemistry and immunofluorescence have emerged as potent tools for the simultaneous detection of multiple protein biomarkers in a single tissue section, thereby expanding opportunities for molecular and immune profiling while preserving tissue samples. By establishing the phenotype of individual tumour cells when distributed within a mixed cell population, the identification of clinically relevant biomarkers with high-throughput multiplex immunophenotyping of tumour samples has great potential to guide appropriate treatment choices. Moreover, the emergence of novel multi-marker imaging approaches can now provide unprecedented insights into the tumour microenvironment, including the potential interplay between various cell types. However, there are significant challenges to widespread integration of these technologies in daily research and clinical practice. This review addresses the challenges and potential solutions within a structured framework of action from a regulatory and clinical trial perspective. New developments within the field of immunophenotyping using multiplexed tissue imaging platforms and associated digital pathology are also described, with a specific focus on translational implications across different subtypes of cancer. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Artificial Intelligence-Powered Assessment of Pathologic Response to Neoadjuvant Atezolizumab in Patients With NSCLC: Results From the LCMC3 Study.

INTRODUCTION: Pathologic response (PathR) by histopathologic assessment of resected specimens may be an early clinical end point associated with long-term outcomes with neoadjuvant therapy. Digital pathology may improve the efficiency and precision of PathR assessment. LCMC3 (NCT02927301) evaluated neoadjuvant atezolizumab in patients with resectable NSCLC and reported a 20% major PathR rate. METHODS: We determined PathR in primary tumor resection specimens using guidelines-based visual techniques and developed a convolutional neural network model using the same criteria to digitally measure the percent viable tumor on whole-slide images. Concordance was evaluated between visual determination of percent viable tumor (n = 151) performed by one of the 47 local pathologists and three central pathologists. RESULTS: For concordance among visual determination of percent viable tumor, the interclass correlation coefficient was 0.87 (95% confidence interval [CI]: 0.84-0.90). Agreement for visually assessed 10% or less viable tumor (major PathR [MPR]) in the primary tumor was 92.1% (Fleiss kappa = 0.83). Digitally assessed percent viable tumor (n = 136) correlated with visual assessment (Pearson r = 0.73; digital/visual slope = 0.28). Digitally assessed MPR predicted visually assessed MPR with outstanding discrimination (area under receiver operating characteristic curve, 0.98) and was associated with longer disease-free survival (hazard ratio [HR] = 0.30; 95% CI: 0.09-0.97, p = 0.033) and overall survival (HR = 0.14, 95% CI: 0.02-1.06, p = 0.027) versus no MPR. Digitally assessed PathR strongly correlated with visual measurements. CONCLUSIONS: Artificial intelligence-powered digital pathology exhibits promise in assisting pathologic assessments in neoadjuvant NSCLC clinical trials. The development of artificial intelligence-powered approaches in clinical settings may aid pathologists in clinical operations, including routine PathR assessments, and subsequently support improved patient care and long-term outcomes.

Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer.

Modern histologic imaging platforms coupled with machine learning methods have provided new opportunities to map the spatial distribution of immune cells in the tumor microenvironment. However, there exists no standardized method for describing or analyzing spatial immune cell data, and most reported spatial analyses are rudimentary. In this review, we provide an overview of two approaches for reporting and analyzing spatial data (raster versus vector-based). We then provide a compendium of spatial immune cell metrics that have been reported in the literature, summarizing prognostic associations in the context of a variety of cancers. We conclude by discussing two well-described clinical biomarkers, the breast cancer stromal tumor infiltrating lymphocytes score and the colon cancer Immunoscore, and describe investigative opportunities to improve clinical utility of these spatial biomarkers. © 2023 The Pathological Society of Great Britain and Ireland.

Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer

The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

GDC-9545 (Giredestrant): A Potent and Orally Bioavailable Selective Estrogen Receptor Antagonist and Degrader with an Exceptional Preclinical Profile for ER+ Breast Cancer.

Breast cancer remains a leading cause of cancer death in women, representing a significant unmet medical need. Here, we disclose our discovery efforts culminating in a clinical candidate, 35 (GDC-9545 or giredestrant). 35 is an efficient and potent selective estrogen receptor degrader (SERD) and a full antagonist, which translates into better antiproliferation activity than known SERDs (1, 6, 7, and 9) across multiple cell lines. Fine-tuning the physiochemical properties enabled once daily oral dosing of 35 in preclinical species and humans. 35 exhibits low drug-drug interaction liability and demonstrates excellent in vitro and in vivo safety profiles. At low doses, 35 induces tumor regressions either as a single agent or in combination with a CDK4/6 inhibitor in an ESR1Y537S mutant PDX or a wild-type ERα tumor model. Currently, 35 is being evaluated in Phase III clinical trials.

A Phase I Study of DLYE5953A, an Anti-LY6E Antibody Covalently Linked to Monomethyl Auristatin E, in Patients with Refractory Solid Tumors.

PURPOSE: DLYE5953A is an antibody-drug conjugate consisting of an anti-LY6E antibody covalently linked to the cytotoxic agent monomethyl auristatin E. This study characterized the safety, pharmacokinetics, immunogenicity, potential biomarkers, and antitumor activity of DLYE5953A in patients with metastatic solid tumors. PATIENTS AND METHODS: This was a phase I, open-label, 3+3 dose-escalation, and dose-expansion study of DLYE5953A administered intravenously every 21 days (Q3W) in patients with locally advanced or metastatic solid malignancies. RESULTS: Sixty-eight patients received DLYE5953A (median, four cycles; range, 1-27). No dose-limiting toxicities were identified during dose escalation (0.2-2.4 mg/kg; n = 20). The recommended phase II dose (RP2D) of 2.4 mg/kg Q3W was based on overall safety and tolerability. Dose-expansion cohorts for HER2-negative metastatic breast cancer (HER2-negative MBC; n = 23) and non-small cell lung cancer (NSCLC; n = 25) patients were enrolled at the RP2D. Among patients receiving DLYE5953A 2.4 mg/kg (n = 55), the most common (≥30%) related adverse events (AEs) included alopecia, fatigue, nausea, and peripheral neuropathy. Grade ≥3 related AEs occurred in 14 of 55 (26%) patients, with neutropenia being the most common (13%). DLYE5953A demonstrated linear total antibody pharmacokinetics at doses of ≥0.8 mg/kg with low unconjugated monomethyl auristatin E levels in blood. Partial response was confirmed in eight of 68 (12%) patients, including three of 29 patients with MBC (10%) and five of 25 patients with NSCLC (20%) at the RP2D. Stable disease was the best response for 37 of 68 (54%) patients. CONCLUSIONS: DLYE5953A administered at 2.4 mg/kg has acceptable safety. Preliminary evidence of antitumor activity in patients with HER2-negative MBC and NSCLC supports further investigation of LY6E as a therapeutic target.

Therapeutic Ligands Antagonize Estrogen Receptor Function by Impairing Its Mobility.

Estrogen receptor-positive (ER+) breast cancers frequently remain dependent on ER signaling even after acquiring resistance to endocrine agents, prompting the development of optimized ER antagonists. Fulvestrant is unique among approved ER therapeutics due to its capacity for full ER antagonism, thought to be achieved through ER degradation. The clinical potential of fulvestrant is limited by poor physicochemical features, spurring attempts to generate ER degraders with improved drug-like properties. We show that optimization of ER degradation does not guarantee full ER antagonism in breast cancer cells; ER "degraders" exhibit a spectrum of transcriptional activities and anti-proliferative potential. Mechanistically, we find that fulvestrant-like antagonists suppress ER transcriptional activity not by ER elimination, but by markedly slowing the intra-nuclear mobility of ER. Increased ER turnover occurs as a consequence of ER immobilization. These findings provide proof-of-concept that small molecule perturbation of transcription factor mobility may enable therapeutic targeting of this challenging target class.

CBP/p300 Drives the Differentiation of Regulatory T Cells through Transcriptional and Non-Transcriptional Mechanisms.

Regulatory T cells (Treg) are immunosuppressive and negatively impact response to cancer immunotherapies. CREB-binding protein (CBP) and p300 are closely related acetyltransferases and transcriptional coactivators. Here, we evaluate the mechanisms by which CBP/p300 regulate Treg differentiation and the consequences of CBP/p300 loss-of-function mutations in follicular lymphoma. Transcriptional and epigenetic profiling identified a cascade of transcription factors essential for Treg differentiation. Mass spectrometry analysis showed that CBP/p300 acetylates prostacyclin synthase, which regulates Treg differentiation by altering proinflammatory cytokine secretion by T and B cells. Reduced Treg presence in tissues harboring CBP/p300 loss-of-function mutations was observed in follicular lymphoma. Our findings provide novel insights into the regulation of Treg differentiation by CBP/p300, with potential clinical implications on alteration of the immune landscape. SIGNIFICANCE: This study provides insights into the dynamic role of CBP/p300 in the differentiation of Tregs, with potential clinical implications in the alteration of the immune landscape in follicular lymphoma.

NRG1 is a critical regulator of differentiation in TP63-driven squamous cell carcinoma.

Squamous cell carcinomas (SCCs) account for the majority of cancer mortalities. Although TP63 is an established lineage-survival oncogene in SCCs, therapeutic strategies have not been developed to target TP63 or it's downstream effectors. In this study we demonstrate that TP63 directly regulates NRG1 expression in human SCC cell lines and that NRG1 is a critical component of the TP63 transcriptional program. Notably, we show that squamous tumors are dependent NRG1 signaling in vivo, in both genetically engineered mouse models and human xenograft models, and demonstrate that inhibition of NRG1 induces keratinization and terminal squamous differentiation of tumor cells, blocking proliferation and inhibiting tumor growth. Together, our findings identify a lineage-specific function of NRG1 in SCCs of diverse anatomic origin.

ER+ Breast Cancers Resistant to Prolonged Neoadjuvant Letrozole Exhibit an E2F4 Transcriptional Program Sensitive to CDK4/6 Inhibitors.

Purpose: This study aimed to identify biomarkers of resistance to endocrine therapy in estrogen receptor-positive (ER+) breast cancers treated with prolonged neoadjuvant letrozole.Experimental Design: We performed targeted DNA and RNA sequencing in 68 ER+ breast cancers from patients treated with preoperative letrozole (median, 7 months).Results: Twenty-four tumors (35%) exhibited a PEPI score ≥4 and/or recurred after a median of 58 months and were considered endocrine resistant. Integration of the 47 most upregulated genes (log FC > 1, FDR < 0.03) in letrozole-resistant tumors with transcription-binding data showed significant overlap with 20 E2F4-regulated genes (P = 2.56E-15). In patients treated with the CDK4/6 inhibitor palbociclib before surgery, treatment significantly decreased expression of 24 of the 47 most upregulated genes in letrozole-resistant tumors, including 18 of the 20 E2F4 target genes. In long-term estrogen-deprived ER+ breast cancer cells, palbociclib also downregulated all 20 E2F4 target genes and P-RB levels, whereas the ER downregulator fulvestrant or paclitaxel only partially suppressed expression of this set of genes and had no effect on P-RB. Finally, an E2F4 activation signature was strongly associated with resistance to aromatase inhibitors in the ACOSOG Z1031B neoadjuvant trial and with an increased risk of relapse in adjuvant-treated ER+ tumors in METABRIC.Conclusions: In tumors resistant to prolonged neoadjuvant letrozole, we identified a gene expression signature of E2F4 target activation. CDK4/6 inhibition suppressed E2F4 target gene expression in estrogen-deprived ER+ breast cancer cells and in patients' ER+ tumors, suggesting a potential benefit of adjuvant CDK4/6 inhibitors in patients with ER+ breast cancer who fail to respond to preoperative estrogen deprivation. Clin Cancer Res; 24(11); 2517-29. ©2018 AACR.

TGFß attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells.

Therapeutic antibodies that block the programmed death-1 (PD-1)-programmed death-ligand 1 (PD-L1) pathway can induce robust and durable responses in patients with various cancers, including metastatic urothelial cancer. However, these responses only occur in a subset of patients. Elucidating the determinants of response and resistance is key to improving outcomes and developing new treatment strategies. Here we examined tumours from a large cohort of patients with metastatic urothelial cancer who were treated with an anti-PD-L1 agent (atezolizumab) and identified major determinants of clinical outcome. Response to treatment was associated with CD8+ T-effector cell phenotype and, to an even greater extent, high neoantigen or tumour mutation burden. Lack of response was associated with a signature of transforming growth factor ß (TGFß) signalling in fibroblasts. This occurred particularly in patients with tumours, which showed exclusion of CD8+ T cells from the tumour parenchyma that were instead found in the fibroblast- and collagen-rich peritumoural stroma; a common phenotype among patients with metastatic urothelial cancer. Using a mouse model that recapitulates this immune-excluded phenotype, we found that therapeutic co-administration of TGFß-blocking and anti-PD-L1 antibodies reduced TGFß signalling in stromal cells, facilitated T-cell penetration into the centre of tumours, and provoked vigorous anti-tumour immunity and tumour regression. Integration of these three independent biological features provides the best basis for understanding patient outcome in this setting and suggests that TGFß shapes the tumour microenvironment to restrain anti-tumour immunity by restricting T-cell infiltration.

MYC and MCL1 Cooperatively Promote Chemotherapy-Resistant Breast Cancer Stem Cells via Regulation of Mitochondrial Oxidative Phosphorylation.

Most patients with advanced triple-negative breast cancer (TNBC) develop drug resistance. MYC and MCL1 are frequently co-amplified in drug-resistant TNBC after neoadjuvant chemotherapy. Herein, we demonstrate that MYC and MCL1 cooperate in the maintenance of chemotherapy-resistant cancer stem cells (CSCs) in TNBC. MYC and MCL1 increased mitochondrial oxidative phosphorylation (mtOXPHOS) and the generation of reactive oxygen species (ROS), processes involved in maintenance of CSCs. A mutant of MCL1 that cannot localize in mitochondria reduced mtOXPHOS, ROS levels, and drug-resistant CSCs without affecting the anti-apoptotic function of MCL1. Increased levels of ROS, a by-product of activated mtOXPHOS, led to the accumulation of HIF-1α. Pharmacological inhibition of HIF-1α attenuated CSC enrichment and tumor initiation in vivo. These data suggest that (1) MYC and MCL1 confer resistance to chemotherapy by expanding CSCs via mtOXPHOS and (2) targeting mitochondrial respiration and HIF-1α may reverse chemotherapy resistance in TNBC.

Genomic profiling of ER+ breast cancers after short-term estrogen suppression reveals alterations associated with endocrine resistance.

Inhibition of proliferation in estrogen receptor-positive (ER+) breast cancers after short-term antiestrogen therapy correlates with long-term patient outcome. We profiled 155 ER+/human epidermal growth factor receptor 2-negative (HER2-) early breast cancers from 143 patients treated with the aromatase inhibitor letrozole for 10 to 21 days before surgery. Twenty-one percent of tumors remained highly proliferative, suggesting that these tumors harbor alterations associated with intrinsic endocrine therapy resistance. Whole-exome sequencing revealed a correlation between 8p11-12 and 11q13 gene amplifications, including FGFR1 and CCND1, respectively, and high Ki67. We corroborated these findings in a separate cohort of serial pretreatment, postneoadjuvant chemotherapy, and recurrent ER+ tumors. Combined inhibition of FGFR1 and CDK4/6 reversed antiestrogen resistance in ER+FGFR1/CCND1 coamplified CAMA1 breast cancer cells. RNA sequencing of letrozole-treated tumors revealed the existence of intrachromosomal ESR1 fusion transcripts and increased expression of gene signatures indicative of enhanced E2F-mediated transcription and cell cycle processes in cancers with high Ki67. These data suggest that short-term preoperative estrogen deprivation followed by genomic profiling can be used to identify druggable alterations that may cause intrinsic endocrine therapy resistance.

Association of FGFR1 with ERα Maintains Ligand-Independent ER Transcription and Mediates Resistance to Estrogen Deprivation in ER+ Breast Cancer.

Purpose:FGFR1 amplification occurs in approximately 15% of estrogen receptor-positive (ER+) human breast cancers. We investigated mechanisms by which FGFR1 amplification confers antiestrogen resistance to ER+ breast cancer.Experimental Design: ER+ tumors from patients treated with letrozole before surgery were subjected to Ki67 IHC, FGFR1 FISH, and RNA sequencing (RNA-seq). ER+/FGFR1-amplified breast cancer cells, and patient-derived xenografts (PDX) were treated with FGFR1 siRNA or the FGFR tyrosine kinase inhibitor lucitanib. Endpoints were cell/xenograft growth, FGFR1/ERα association by coimmunoprecipitation and proximity ligation, ER genomic activity by ChIP sequencing, and gene expression by RT-PCR.Results: ER+/FGFR1-amplified tumors in patients treated with letrozole maintained cell proliferation (Ki67). Estrogen deprivation increased total and nuclear FGFR1 and FGF ligands expression in ER+/FGFR1-amplified primary tumors and breast cancer cells. In estrogen-free conditions, FGFR1 associated with ERα in tumor cell nuclei and regulated the transcription of ER-dependent genes. This association was inhibited by a kinase-dead FGFR1 mutant and by treatment with lucitanib. ChIP-seq analysis of estrogen-deprived ER+/FGFR1-amplified cells showed binding of FGFR1 and ERα to DNA. Treatment with fulvestrant and/or lucitanib reduced FGFR1 and ERα binding to DNA. RNA-seq data from FGFR1-amplified patients' tumors treated with letrozole showed enrichment of estrogen response and E2F target genes. Finally, growth of ER+/FGFR1-amplified cells and PDXs was more potently inhibited by fulvestrant and lucitanib combined than each drug alone.Conclusions: These data suggest the ERα pathway remains active in estrogen-deprived ER+/FGFR1-amplified breast cancers. Therefore, these tumors are endocrine resistant and should be candidates for treatment with combinations of ER and FGFR antagonists. Clin Cancer Res; 23(20); 6138-50. ©2017 AACR.