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.

An Open-label Phase I Study of GDC-0927 in Postmenopausal Women with Locally Advanced or Metastatic Estrogen Receptor-Positive Breast Cancer.

PURPOSE: GDC-0927 is a novel, potent, nonsteroidal, orally bioavailable, selective estrogen receptor (ER) degrader that induces tumor regression in ER+ breast cancer xenograft models. PATIENTS AND METHODS: This phase I dose-escalation multicenter study enrolled postmenopausal women with ER+/HER2- metastatic breast cancer to determine the safety, pharmacokinetics, and recommended phase II dose of GDC-0927. Pharmacodynamics was assessed with [18F]-fluoroestradiol (FES) PET scans. RESULTS: Forty-two patients received GDC-0927 once daily. The MTD was not reached. The most common adverse events (AE) regardless of causality were nausea, constipation, diarrhea, arthralgia, fatigue, hot flush, back pain, and vomiting. There were no deaths, grade 4/5 AEs, or treatment-related serious AEs. Two patients experienced grade 2 AEs of special interest of deep vein thrombosis and jugular vein thrombosis, both considered unrelated to GDC-0927. Following dosing, approximately 1.6-fold accumulation was observed, consistent with the observed half-life and dosing frequency. There were no complete or partial responses. Pharmacodynamics was supported by >90% reduction in FES uptake and an approximately 40% reduction in ER expression, suggesting ER degradation is not the mechanistic driver of ER antagonism. Twelve patients (29%) achieved clinical benefit; 17 patients (41%) showed a confirmed best overall response of stable disease. Baseline levels of ER and progesterone receptor protein and mutant ESR1 circulating tumor DNA did not correlate with clinical benefit. CONCLUSIONS: GDC-0927 appeared to be well tolerated with pharmacokinetics supporting once-daily dosing. There was evidence of target engagement and preliminary evidence of antitumor activity in heavily pretreated patients with advanced/metastatic ER+/HER2- breast cancer with and without ESR1 mutations.

The oral selective estrogen receptor degrader GDC-0810 (ARN-810) in postmenopausal women with hormone receptor-positive HER2-negative (HR + /HER2 -) advanced/metastatic breast cancer.

PURPOSE: GDC-0810 (ARN-810) is a novel, non-steroidal, orally bioavailable, selective estrogen receptor degrader (SERD) that potentially inhibits ligand-dependent and ligand-independent estrogen receptor (ER)-mediated signaling. METHODS: A phase Ia/Ib/IIa dose escalation, combination treatment with palbociclib or a luteinizing hormone-releasing hormone, and expansion study determined the safety, pharmacokinetics, and recommended phase 2 dose (RP2D) of GDC-0810 in postmenopausal women with ER + (HER2 -) locally advanced or metastatic breast cancer (MBC). Baseline plasma ctDNA samples were analyzed to determine the ESR1 mutation status. RESULTS: Patients (N = 152) received GDC-0810 100-800 mg once daily (QD) or 300-400 mg twice daily, in dose escalation, expansion, as single agent or combination treatment. Common adverse events regardless of attribution to study drug were diarrhea, nausea, fatigue, vomiting, and constipation. There was one dose-limiting toxicity during dose escalation. The maximum tolerated dose was not reached. GDC-0810 600 mg QD taken with food was the RP2D. Pharmacokinetics were predictable. FES reduction (> 90%) highlighting pharmacodynamic engagement of ER was observed. Outcomes for the overall population and for patients with tumors harboring ESR1 mutations included partial responses (4% overall; 4% ESR1), stable disease (39% overall; 42% ESR1), non-complete response/non-progressive disease (13% overall; 12% ESR1), progressive disease (40% overall; 38% ESR1), and missing/unevaluable (5% overall; 5% ESR1). Clinical benefit (responses or SD, lasting ≥ 24 weeks) was observed in patients in dose escalation (n = 16, 39%) and expansion (n = 24, 22%). CONCLUSION: GDC-0810 was safe and tolerable with preliminary anti-tumor activity in heavily pretreated patients with ER + advanced/MBC, with/without ESR1 mutations, highlighting the potential for oral SERDs. Clinical Trial and registration date April 4, 2013. NCT01823835 .

Giredestrant reverses progesterone hypersensitivity driven by estrogen receptor mutations in breast cancer.

ESR1 (estrogen receptor 1) hotspot mutations are major contributors to therapeutic resistance in estrogen receptor-positive (ER+) breast cancer. Such mutations confer estrogen independence to ERα, providing a selective advantage in the presence of estrogen-depleting aromatase inhibitors. In addition, ESR1 mutations reduce the potency of tamoxifen and fulvestrant, therapies that bind ERα directly. These limitations, together with additional liabilities, inspired the development of the next generation of ERα-targeted therapeutics, of which giredestrant is a high-potential candidate. Here, we generated Esr1 mutant-expressing mammary gland models and leveraged patient-derived xenografts (PDXs) to investigate the biological properties of the ESR1 mutations and their sensitivity to giredestrant in vivo. In the mouse mammary gland, Esr1 mutations promote hypersensitivity to progesterone, triggering pregnancy-like tissue remodeling and profoundly elevated proliferation. These effects were driven by an altered progesterone transcriptional response and underpinned by gained sites of ERα-PR (progesterone receptor) cobinding at the promoter regions of pro-proliferation genes. PDX experiments showed that the mutant ERα-PR proliferative program is also relevant in human cancer cells. Giredestrant suppressed the mutant ERα-PR proliferation in the mammary gland more so than the standard-of-care agents, tamoxifen and fulvestrant. Giredestrant was also efficacious against the progesterone-stimulated growth of ESR1 mutant PDX models. In addition, giredestrant demonstrated activity against a molecularly characterized ESR1 mutant tumor from a patient enrolled in a phase 1 clinical trial. Together, these data suggest that mutant ERα can collaborate with PR to drive protumorigenic proliferation but remain sensitive to inhibition by giredestrant.

Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer.

Inhibitors of the programmed cell death-1 (PD-1/PD-L1) signaling axis are approved to treat non-small cell lung cancer (NSCLC) patients, based on their significant overall survival (OS) benefit. Using transcriptomic analysis of 891 NSCLC tumors from patients treated with either the PD-L1 inhibitor atezolizumab or chemotherapy from two large randomized clinical trials, we find a significant B cell association with extended OS with PD-L1 blockade, independent of CD8+ T cell signals. We then derive gene signatures corresponding to the dominant B cell subsets present in NSCLC from single-cell RNA sequencing (RNA-seq) data. Importantly, we find increased plasma cell signatures to be predictive of OS in patients treated with atezolizumab, but not chemotherapy. B and plasma cells are also associated with the presence of tertiary lymphoid structures and organized lymphoid aggregates. Our results suggest an important contribution of B and plasma cells to the efficacy of PD-L1 blockade in NSCLC.

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.

Single-cell dissection of cellular components and interactions shaping the tumor immune phenotypes in ovarian cancer.

Distinct T cell infiltration patterns, i.e., immune infiltrated, excluded, and desert, result in different responses to cancer immunotherapies. However, the key determinants and biology underpinning these tumor immune phenotypes remain elusive. Here, we provide a high-resolution dissection of the entire tumor ecosystem through single-cell RNA-sequencing analysis of 15 ovarian tumors. Immune-desert tumors are characterized by unique tumor cell-intrinsic features, including metabolic pathways and low antigen presentation, and an enrichment of monocytes and immature macrophages. Immune-infiltrated and -excluded tumors differ markedly in their T cell composition and fibroblast subsets. Furthermore, our study reveals chemokine receptor-ligand interactions within and across compartments as potential mechanisms mediating immune cell infiltration, exemplified by the tumor cell-T cell cross talk via CXCL16-CXCR6 and stromal-immune cell cross talk via CXCL12/14-CXCR4. Our data highlight potential molecular mechanisms that shape the tumor immune phenotypes and may inform therapeutic strategies to improve clinical benefit from cancer immunotherapies.

Automated Dissection Protocol for Tumor Enrichment in Low Tumor Content Tissues.

Tumor enrichment in low tumor content tissues, those below 20% tumor content depending on the method, is required to generate quality data reproducibly with many downstream assays such as next generation sequencing. Automated tissue dissection is a new methodology that automates and improves tumor enrichment in these common, low tumor content tissues by decreasing the user-dependent imprecision of traditional macro-dissection and time, cost, and expertise limitations of laser capture microdissection by using digital image annotation overlay onto unstained slides. Here, digital hematoxylin and eosin (H&E) annotations are used to target small tumor areas using a blade that is 250 µm2 in diameter in unstained formalin fixed paraffin embedded (FFPE) or fresh frozen sections up to 20 µm in thickness for automated tumor enrichment prior to nucleic acid extraction and whole exome sequencing (WES). Automated dissection can harvest annotated regions in low tumor content tissues from single or multiple sections for nucleic acid extraction. It also allows for capture of extensive pre- and post-harvest collection metrics while improving accuracy, reproducibility, and increasing throughput with utilization of fewer slides. The described protocol enables digital annotation with automated dissection on animal and/or human FFPE or fresh frozen tissues with low tumor content and could also be used for any region of interest enrichment to boost adequacy for downstream sequencing applications in clinical or research workflows.

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.