Tumor-agnostic transcriptome-based classifier identifies spatial infiltration patterns of CD8+T cells in the tumor microenvironment and predicts clinical outcome in early-phase and late-phase clinical trials.

BACKGROUND: The immune status of a patient's tumor microenvironment (TME) may guide therapeutic interventions with cancer immunotherapy and help identify potential resistance mechanisms. Currently, patients' immune status is mostly classified based on CD8+tumor-infiltrating lymphocytes. An unmet need exists for comparable and reliable precision immunophenotyping tools that would facilitate clinical treatment-relevant decision-making and the understanding of how to overcome resistance mechanisms. METHODS: We systematically analyzed the CD8 immunophenotype of 2023 patients from 14 phase I-III clinical trials using immunohistochemistry (IHC) and additionally profiled gene expression by RNA-sequencing (RNA-seq). CD8 immunophenotypes were classified by pathologists into CD8-desert, CD8-excluded or CD8-inflamed tumors using CD8 IHC staining in epithelial and stromal areas of the tumor. Using regularized logistic regression, we developed an RNA-seq-based classifier as a surrogate to the IHC-based spatial classification of CD8+tumor-infiltrating lymphocytes in the TME. RESULTS: The CD8 immunophenotype and associated gene expression patterns varied across indications as well as across primary and metastatic lesions. Melanoma and kidney cancers were among the strongest inflamed indications, while CD8-desert phenotypes were most abundant in liver metastases across all tumor types. A good correspondence between the transcriptome and the IHC-based evaluation enabled us to develop a 92-gene classifier that accurately predicted the IHC-based CD8 immunophenotype in primary and metastatic samples (area under the curve inflamed=0.846; excluded=0.712; desert=0.855). The newly developed classifier was prognostic in The Cancer Genome Atlas (TCGA) data and predictive in lung cancer: patients with predicted CD8-inflamed tumors showed prolonged overall survival (OS) versus patients with CD8-desert tumors (HR 0.88; 95% CI 0.80 to 0.97) across TCGA, and longer OS on immune checkpoint inhibitor administration (phase III OAK study) in non-small-cell lung cancer (HR 0.75; 95% CI 0.58 to 0.97). CONCLUSIONS: We provide a new precision immunophenotyping tool based on gene expression that reflects the spatial infiltration patterns of CD8+ lymphocytes in tumors. The classifier enables multiplex analyses and is easy to apply for retrospective, reverse translation approaches as well as for prospective patient enrichment to optimize the response to cancer immunotherapy.

Translation and evaluation of a pre-clinical 5-protein response prediction signature in a breast cancer phase Ib clinical trial.

Human protein biomarker discovery relies heavily on pre-clinical models, in particular established cell lines and patient-derived xenografts, but confirmation studies in primary tissue are essential to demonstrate clinical relevance. We describe in this study the process that was followed to clinically translate a 5-protein response signature predictive for the activity of an anti-HER3 monoclonal antibody (lumretuzumab) originally measured in fresh frozen xenograft tissue. We detail the development, qualification, and validation of the multiplexed targeted mass spectrometry assay used to assess the signature performance in formalin-fixed, paraffin-embedded human clinical samples collected in a phase Ib trial designed to evaluate lumretuzumab in patients with metastatic breast cancer. We believe that the strategy delineated here provides a path forward to avoid the time- and cost-consuming step of having to develop immunological reagents against unproven targets. We expect that mass spectrometry-based platforms may become part of a rational process to rapidly test and qualify large number of candidate biomarkers to identify the few that stand a chance for further development and validation.

Detection of truncated HER2 forms in formalin-fixed, paraffin-embedded breast cancer tissue captures heterogeneity and is not affected by HER2-targeted therapy.

Truncated forms of HER2, previously identified in subsets of HER2-positive breast cancer, originate from proteolytic extracellular domain (ECD) cleavage or alternative translation initiation. They lack ECD but may retain intracellular domain functionality, potentially associated with unfavorable prognosis, metastasis, and decreased sensitivity to antibody-based HER2-targeted therapy. To study the distribution of truncated HER2 in breast cancer, we detected loss of membrane-bound ECD independently of its molecular origin in paraffin sections, combining multispectral unmixing of chromogenic duplex IHC for HER2 ECD and intracellular domain with advanced image analysis. HER2 C-terminal fragment 611-transfected MCF7 and 4-aminophenylmercuric acetate-treated SKBR3 cell lines were used as controls. Applying a prototype work flow to whole sections, paired surgical resection/core needle biopsy samples, and paired samples from 69 patients of a phase 2 neoadjuvant clinical trial, we observed unexpected heterogeneity of ECD loss at the single-cell level, and in different areas of individual tumors, indicating that extent and localization of HER2 ECD loss add relevant information to averaging truncated HER2 across whole sections. We show acceptable run-to-run variation (coefficient of variation, <0.15), image analysis results in moderate agreement with conventional slide assessment (Cohen's κ = 0.59), and no obvious interference with previous HER2-ECD-targeted therapy. We conclude that duplex IHC and digital image processing extend current approaches of truncated HER2 detection.

Combat or surveillance? Evaluation of the heterogeneous inflammatory breast cancer microenvironment.

Evaluation of specific lymphocyte subsets is important in understanding the microenvironment in cancer and holds promise as a prognostic parameter in invasive breast cancer. To address this, we used digital image analysis to integrate cell abundance, distance metrics, neighbourhood relationships and sample heterogeneity into comprehensive assessment of immune infiltrates. Lymphocyte and macrophage subpopulations were detected by chromogenic duplex immunohistochemistry for CD3/perforin and CD68/CD163 in samples of invasive breast cancer. The analysis workflow combined commercial and open-source software modules. We confirmed the accuracy of automated detection of cells with lymphoid morphology [concordance correlation coefficient (CCC), 0.92 for CD3(+) -T lymphocytes], whereas variable morphology limited automated classification of macrophages as distinct cellular objects (CCC, 0.43 for object-based detection; 0.79 for pixel-based area analysis). Using a supervised learning algorithm that clustered image areas according to lymphocyte abundance, grouping behaviour and distance to tumour cells, we identified recurrent infiltration patterns reflecting different grades of direct interaction between tumour and immune effector cells. The approach provided comprehensive visual and statistical assessment of the inflammatory tumour microenvironment and allowed quantitative estimation of heterogeneous immune cell distribution. Cases with dense lymphocytic infiltrates (8/33) contained up to 65% of areas in which observed distances between tumour and immune cells suggested a low chance of direct contact, indicating the presence of regions where tumour cells might be protected from immune attack. In contrast, cases with moderate (11/33) or low (14/33) lymphocyte density occasionally comprised areas of focally intense interaction, likely not to be captured by conventional scores. Our approach improves the conventional evaluation of immune cell density scores by translating objective distance metrics into reproducible, largely observer-independent interaction patterns.

Effects of cold ischemia and inflammatory tumor microenvironment on detection of PI3K/AKT and MAPK pathway activation patterns in clinical cancer samples.

The accuracy of common markers for PI3K/AKT and MAPK pathway activation in preclinical and clinical cancer biomarker studies depends on phosphoepitope stability and changes of phosphorylation under ischemia. Herein, we define conditions under which phosphoepitope-specific duplex immunohistochemistry (IHC) on formalin-fixed, paraffin-embedded tumor tissues reflects pathway activation in situ as accurately as possible, and identify activation patterns linked to mutational status, pathway dependency and tumor microenvironment in clinical tumor samples, cell culture and xenograft tissues. Systematically assessing robustness of pAKT, pERK1/2, pMEK1/2 and pmTOR detection and related markers in xenograft tissues exposed to ischemia, we show that control of preprocessing and ischemia times allows accurate interpretation of staining results. Phosphorylation patterns were then analyzed in 33 xenograft models and in 58 cases with breast cancer, including 21 paired samples of core-needle biopsies with corresponding mastectomy specimens, and 37 mastectomy samples obtained under rigorously controlled conditions minimizing ischemia time. Patterns of pAKT and pERK1/2 staining (predominant PI3K/AKT, predominant MAPK and concomitant activation) were associated with sensitivity to pathway inhibition and partially with the mutational status in cell lines and corresponding xenograft tumors. In contrast, no clear correlation between mutational status and staining patterns was observed in clinical breast cancer samples, suggesting that interaction with the human tumor microenvironment may interfere with the use of phosphoepitope-specific IHC as potential markers for pathway dependency. In contrast to core needle biopsies, surgically resected breast cancer samples showed evidence of severe signal changes comparable to those effects observed in xenograft tumors exposed to controlled ischemia.