Interassay and interobserver comparability study of four programmed death-ligand 1 (PD-L1) immunohistochemistry assays in triple-negative breast cancer

Positivity Rate of PD-L1 Expression and Its Clinical Significance in Vulvar Cancer: A Systematic Review and Meta-Analysis

The prevalence and prognostic value of programmed death ligand 1 (PD-L1) expression, as a potential biomarker in vulvar squamous cell carcinomas (VSCCs), remain underexplored. We searched the PubMed, Scopus, Embase, and Cochrane Library databases until July 2024 for articles examining PD-L1 expression in VSCCs. Random-effects meta-analyses summarized PD-L1 expression overall and in subgroups by immunohistochemistry antibody type, positivity cutoff, tumor stage, and HPV positivity. Additionally, random-effects meta-analyses summarized the association between PD-L1 positivity and cancer prognosis. We included 26 studies comprising 1912 VSCC cases. The summary PD-L1 positivity rate in tumor cells was 59.9% (95% confidence interval [CI]: 47.7-71.4%; I2 = 96%, n = 26), influenced by the different cutoff thresholds utilized to define PD-L1 positivity. Compared to tumor cells, positivity rates were higher in intratumoral immune cells (75.6%; 95%CI: 52.9-92.5; I2 = 95.4%, n = 6) and peritumoral cells (78.9%; 95%CI: 54.4-95.5%; I2 = 91%, n = 3) but with overlapping 95%CIs. No heterogeneity was observed in the rates by tumor stage or HPV status. Positive PD-L1 expression was associated with worse overall (hazard ratio [HR] = 1.43; 95%CI: 1.06-1.93; I2 = 28.9%, n = 7) and progression-free survival (HR = 1.57; 95%CI: 1.07-2.3; I2 = 38.3%, n = 5). The PD-L1 expression rate in VSCC tumor cells varied across studies, was influenced by differences in immunohistochemical evaluation, and was identified as an unfavorable prognostic factor. Large, prospective, multicenter studies with standardized protocols are crucial to further elucidate the clinical significance of PD-L1 expression in VSCCs.

Society for Immunotherapy of Cancer (SITC) consensus statement on essential biomarkers for immunotherapy clinical protocols

Immunotherapy of cancer is now an essential pillar of treatment for patients with many individual tumor types. Novel immune targets and technical advances are driving a rapid exploration of new treatment strategies incorporating immune agents in cancer clinical practice. Immunotherapies perturb a complex system of interactions among genomically unstable tumor cells, diverse cells within the tumor microenvironment including the systemic adaptive and innate immune cells. The drive to develop increasingly effective immunotherapy regimens is tempered by the risk of immune-related adverse events. Evidence-based biomarkers that measure the potential for therapeutic response and/or toxicity are critical to guide optimal patient care and contextualize the results of immunotherapy clinical trials. Responding to the lack of guidance on biomarker testing in early-phase immunotherapy clinical trials, we propose a definition and listing of essential biomarkers recommended for inclusion in all such protocols. These recommendations are based on consensus provided by the Society for Immunotherapy of Cancer (SITC) Clinical Immuno-Oncology Network (SCION) faculty with input from the SITC Pathology and Biomarker Committees and the Journal for ImmunoTherapy of Cancer readership. A consensus-based selection of essential biomarkers was conducted using a Delphi survey of SCION faculty. Regular updates to these recommendations are planned. The inaugural list of essential biomarkers includes complete blood count with differential to generate a neutrophil-to-lymphocyte ratio or systemic immune-inflammation index, serum lactate dehydrogenase and albumin, programmed death-ligand 1 immunohistochemistry, microsatellite stability assessment, and tumor mutational burden. Inclusion of these biomarkers across early-phase immunotherapy clinical trials will capture variation among trials, provide deeper insight into the novel and established therapies, and support improved patient selection and stratification for later-phase clinical trials.

Challenges to Innovation Arising from Current Companion Diagnostic Regulations and Suggestions for Improvements

A companion diagnostic is a diagnostic test that provides information essential for the safe and effective use of a corresponding therapeutic product. To obtain marketing approval, the companion diagnostic must demonstrate acceptable analytical and clinical performance. Companion diagnostic regulations are intended to protect patients by ensuring quality and consistency of treatment-guiding biomarker testing in clinical trials and clinical practice. However, current regulations have had unintended negative consequences relating to innovation, implementation, and accessibility of precision medicine; increasing complexity and cost burden; and inhibiting development of novel diagnostics and biomarker-targeted therapeutics. We propose a range of practical solutions to these challenges, advocating that regulators, pharmaceutical companies, molecular pathologist groups, and diagnostic companies work together to increase flexibility and promote diagnostic innovation, while maintaining high-quality diagnostic testing to ensure all patients get the most appropriate treatments.

Inherent PD-L1 22C3 Expression in Alveolar Macrophages Impacts the Combined Positive Score Status in Breast Cancer With Pulmonary Metastasis

PURPOSE

This study aimed to determine the impact of inherent programmed death-ligand 1 (PD-L1)-expressing alveolar macrophages (AMs) on the combined positive score (CPS) of PD-L1 (22C3) in metastatic breast cancer in the lungs.

METHODS

A total of 87 patients with pulmonary metastases of breast cancer were included in this study. Immunohistochemical staining of various PD-L1 antibodies was performed. The CPSs and CPSs excluding the number of PD-L1 positive AMs [CPS(NAM)s] with PD-L1 (22C3) were determined and compared.

RESULTS

Among 87 enrolled patients, 22 had luminal A breast cancer, 24 had luminal B breast cancer, 13 had HER-2-positive breast cancer, and 28 had triple-negative breast cancer (TNBC). CPSs ≥ 10 was observed only in luminal B (12.5%) and TNBC (35.7%) subtypes (p < 0.001), whereas CPS(NAM)s ≥ 10 was observed only in TNBC (14.3%) (p = 0.011). Changes from the CPS-positive to the CPS(NAM)-negative status occurred in nine cases (10.3%), with significantly higher proportions being observed in the luminal B (12.5%) and TNBC (21.4%) subtypes (p = 0.007). Tumors showing changes from the CPS-positive to the CPS(NAM)-negative status were larger (p < 0.001); similar findings were observed in the TNBC subgroup (p = 0.001).

CONCLUSION

The inclusion of PD-L1 expressing AMs leads to differences in CPS positivity, especially in large TNBC subtype tumors.

Autofluorescence Virtual Staining System for H&E Histology and Multiplex Immunofluorescence Applied to Immuno-Oncology Biomarkers in Lung Cancer

SIGNIFICANCE

We extend the capabilities of virtual staining from AF to a different disease and stain modality. Our work includes newly developed virtual stains for H&E and a multiplex immunofluorescence panel (DAPI, PanCK, PD-L1, CD3, and CD8) for non-small cell lung cancer, which reproduce the key features of real stains.

Expression of PD-L1 in breast invasive lobular carcinoma

PURPOSE

The purpose of this study was to investigate the expression of PD-L1 in invasive lobular carcinoma (ILC) and to determine its implications.

METHODS

Tissue microarrays were constructed for 101 cases of ILC, and immunohistochemical staining for PD-L1 (using 22C3, SP142, and SP263 antibodies) was performed to examine the correlation between staining results and clinicopathologic parameters.

RESULTS

The positive cut-off values were defined as tumor cell (TC)≥1%, immune cell (IC)>0%, and IC≥1%. The range of PD-L1 TC positivity was 0.0-2.0%, with PD-L1 SP263 TC showing the highest positivity of 2.0%. The range of PD-L1 IC positivity was 0-21.8% for IC ≥ 1%, with PD-L1 22C3 IC showing the highest positivity. When PD-L1 IC was positive (IC≥1%), the highest antibody agreement was observed between SP263 and SP142 (OA = 93.1%), while the lowest agreement was observed between 22C3 and SP263 (OA = 73.3%, κ = 0.040). PD-L1 22C3 IC positivity (≥1%) was associated with high nuclear grade (p = 0.002), HER-2 positivity (p = 0.019), and pleomorphic type (p = 0.002).

CONCLUSION

PD-L1 expression in ILC shows a low TC positivity rate (0-2%) with various antibody clones and a variable IC positivity rate (0-21.8%). Pleomorphic type ILC exhibits higher PD-L1 IC positivity.

Improving efficacy of TNBC immunotherapy: based on analysis and subtyping of immune microenvironment

Triple-negative breast cancer (TNBC) is a highly aggressive type of breast cancer that encompasses several distinct subtypes. Recent advances in immunotherapy offer a promising future for the treatment of these highly heterogeneous and readily metastatic tumors. Despite advancements, the efficacy of immunotherapy remains limited as shown by unimproved efficacy of PD-L1 biomarker and limited patient benefit. To enhance the effectiveness of TNBC immunotherapy, we conducted investigation on the microenvironment, and corresponding therapeutic interventions of TNBC and recommended further investigation into the identification of additional biomarkers that can facilitate the subtyping of TNBC for more targeted therapeutic approaches. TNBC is a highly aggressive subtype with dismal long-term survival due to the lack of opportunities for traditional endocrine and targeted therapies. Recent advances in immunotherapy have shown promise, but response rates can be limited due to the heterogeneous tumor microenvironments and developed therapy resistance, especially in metastatic cases. In this review, we will investigate the tumor microenvironment of TNBC and corresponding therapeutic interventions. We will summarize current subtyping strategies and available biomarkers for TNBC immunotherapy, with a particular emphasis on the need for further research to identify additional prognostic markers and refine tailored therapies for specific TNBC subtypes. These efforts aim to improve treatment sensitivity and ultimately enhance survival outcomes for advanced-stage TNBC patients.

Artificial intelligence enhances whole-slide interpretation of PD-L1 CPS in triple-negative breast cancer: A multi-institutional ring study

BACKGROUND AND AIMS

Evaluation of the programmed cell death ligand-1 (PD-L1) combined positive score (CPS) is vital to predict the efficacy of the immunotherapy in triple-negative breast cancer (TNBC), but pathologists show substantial variability in the consistency and accuracy of the interpretation. It is of great importance to establish an objective and effective method which is highly repeatable.

METHODS

We proposed a model in a deep learning-based framework, which at the patch level incorporated cell analysis and tissue region analysis, followed by the whole-slide level fusion of patch results. Three rounds of ring studies (RSs) were conducted. Twenty-one pathologists of different levels from four institutions evaluated the PD-L1 CPS in TNBC specimens as continuous scores by visual assessment and our artificial intelligence (AI)-assisted method.

RESULTS

In the visual assessment, the interpretation results of PD-L1 (Dako 22C3) CPS by different levels of pathologists have significant differences and showed weak consistency. Using AI-assisted interpretation, there were no significant differences between all pathologists (P = 0.43), and the intraclass correlation coefficient (ICC) value was increased from 0.618 [95% confidence interval (CI) = 0.524-0.719] to 0.931 (95% CI = 0.902-0.955). The accuracy of interpretation result is further improved to 0.919 (95% CI = 0.886-0.947). Acceptance of AI results by junior pathologists was the highest among all levels, and 80% of the AI results were accepted overall.

CONCLUSION

With the help of the AI-assisted diagnostic method, different levels of pathologists achieved excellent consistency and repeatability in the interpretation of PD-L1 (Dako 22C3) CPS. Our AI-assisted diagnostic approach was proved to strengthen the consistency and repeatability in clinical practice.

An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability

AIMS

Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between pathologists due to the consideration of both immune and tumour cell positivity.

METHODS AND RESULTS

An artificial intelligence (AI)-powered PD-L1 CPS analyser was developed using 1,275,907 cells and 6175.42 mm2 of tissue annotated by pathologists, extracted from 400 PD-L1 22C3-stained whole slide images of UC. We validated the AI model on 543 UC PD-L1 22C3 cases collected from three institutions. There were 446 cases (82.1%) where the CPS results (CPS ≥10 or <10) were in complete agreement between three pathologists, and 486 cases (89.5%) where the AI-powered CPS results matched the consensus of two or more pathologists. In the pathologist's assessment of the CPS, statistically significant differences were noted depending on the source hospital (P = 0.003). Three pathologists reevaluated discrepancy cases with AI-powered CPS results. After using the AI as a guide and revising, the complete agreement increased to 93.9%. The AI model contributed to improving the concordance between pathologists across various factors including hospital, specimen type, pathologic T stage, histologic subtypes, and dominant PD-L1-positive cell type. In the revised results, the evaluation discordance among slides from different hospitals was mitigated.

CONCLUSION

This study suggests that AI models can help pathologists to reduce discrepancies between pathologists in quantifying immunohistochemistry including PD-L1 22C3 CPS, especially when evaluating data from different institutions, such as in a telepathology setting.

Clinical effectiveness and safety of gemcitabine plus capecitabine in the treatment of advanced triple-negative breast cancer

PURPOSE

To determine the clinical effectiveness and safety of Gemcitabine (GEM) plus Capecitabine (CAP) for advanced triple-negative breast cancer (aTNBC).

METHODS

Eighty aTNBC patients treated in Affiliated Hospital of Nanjing Medical University between June 2020 and June 2022 were retrospectively included and divided into an observation group (Obs; 42 cases treated with GEM + CAP) and a control group (Con; 38 cases treated with docetaxel + CAP) according to different chemotherapy regimens. The clinical effectiveness and the serum levels of tumor markers and inflammatory factors pre- and post-treatment were detected for comparative analyses. In addition, the two groups were compared in terms of side effects, 1-year survival, and quality of life after 1 month of treatment. Cox regression was performed to identify the independent risk factors affecting patient prognosis.

RESULTS

Higher clinical effectiveness was observed in the Obs group compared to the Con (P < 0.05). The pre-treatment TPS, CA153, TNF-α, and IL-6 levels were comparable between groups (all P > 0.05); however, better post-treatment TPS, CA153, and inflammatory factors were observed in the Obs group compared to the Con (all P < 0.05). The Obs group also showed markedly lower drug-induced toxicities than the Con group, with higher 1-year survival and better quality-of-life after 1 month of treatment (all P < 0.05). According to multivariate analysis, clinical stage and lymph node metastasis were independent risk factors for poor prognosis, and GEM + CAP chemotherapy was a protective prognostic factor.

CONCLUSIONS

GEM + CAP is effective in treating aTNBC and provides clinical benefit for patients, with fewer side effects and good patient tolerance.

Comparison of assessment of programmed death-ligand 1 (PD-L1) status in triple-negative breast cancer biopsies and surgical specimens

AIMS

Programmed death-ligand 1 (PD-L1) status in triple-negative breast cancer (TNBC) is important for immune checkpoint inhibitor therapies but may vary between different immunohistochemical assays, scorings and the type of specimen used for analysis.

METHODS

We compared the analytical concordance of three clinically relevant PD-L1 assays (VENTANA SP142, VENTANA SP263 and DAKO 22C3 pharmDx) assessing immune cell score (IC), tumour proportion score and combined positive score (CPS) in preoperative biopsies and resection specimens of primary TNBC. PD-L1 expression was scored on virtual whole slide images and compared with expression data from corresponding surgical specimens.

RESULTS

The mean PD-L1 positivity in TNBC biopsies defined as IC ≥1% and CPS ≥1 ranged between 11% and 61% with the lowest positivity for SP142 and highest for SP263. The corresponding surgical specimens showed overall higher positivity rates (53%-75%). When comparing biopsies with surgical specimens, the agreement for PD-L1 positivity with SP263 and 22C3 at IC score ≥1% and CPS ≥1 was fair (kappa 0.47-0.52) and poor for SP142 (kappa 0.15-0.19). Using CPS ≥10 cut-off, the agreement for SP263 was excellent (kappa 0.751) but poor for 22C3 (kappa 0.261). Spearman correlation coefficients ranged between 0.489 and 0.75 indicating a generally moderate to strong correlation between biopsies and surgical specimens for all assays and scores.

CONCLUSIONS

We demonstrate high accordance between biopsies and surgical specimens for SP263 and 22C3 scoring but less for SP142. Generally, biopsies are suitable for PD-L1 testing in TNBC but the appropriate assay, scoring and cut-off must be considered.

PD-L1 testing in metastatic triple-negative breast cancer: Interobserver and interplatform reproducibility of CE-IVD assays for CPS and IC scores

PD-L1 test is recommended in different types of tumors to select patients eligible for immune checkpoint inhibitors (ICI) therapy. Several factors make this test challenging in metastatic triple-negative breast cancer (mTNBC). Different assays and platforms are available, each associated with distinct scoring systems and threshold values specific to the ICI compound used, i.e. CPS≥10 for pembrolizumab and IC ≥ 1 % for atezolizumab. Our objective was to assess the consistency of PD-L1 testing in mTNBC by examining interobserver and interassay reproducibility. We assessed n = 60 mTNBC samples for PD-L1 testing using 22C3 pharmDx assay on a Dako Autostainer Link 48 and VENTANA PD-L1 (SP263) on a Ventana BenchMark Ultra. Additionally, a subset of n = 19 samples was tested using the SP142 assay, also on the Ventana BenchMark Ultra. CPS with both 22C3 and SP263 was independently evaluated by five pathologists, all certified PD-L1 trainers. The IC with SP142 was assessed by three of these pathologists, who have particular expertise in breast pathology. Following the computation of the intraclass correlation coefficient (ICC) for each assay and their respective thresholds, we assessed the agreement between different raters and assays using Fleiss's κ, with a 95 % confidence interval (CI). Overall, we observed a significant (p < 0.001) ICC with both CPS assays [22C3 = 0.939 (CI:0.913-0.96); SP263 = 0.972 (CI:0.96-0.982); combined 22C3-SP263 = 0.909 (CI:0.874-0.938)]. Fleiss's κ confirmed an almost perfect agreement among pathologists and assays: 22C3 = 0.938 (CI:0.857-1.018); SP263 = 0.972 (CI:0.890-1.052); combined 22C3-SP263 = 0.907 (CI:0.869-0.945). Perfect inter-rater agreement was reached considering IC. This study establishes the reliability of assessing CPS in mTNBC using either the 22C3 pharmDx, as employed in the KEYNOTE studies, or the VENTANA SP263 assay. Each assay must be used on its designated platform, namely the Dako for 22C3 pharmDx and the Ventana for VENTANA SP263. It is important to remark that CPS and IC identify different patient cohorts and, therefore, are not interchangeable.

Comparison of SP142 and 22C3 PD-L1 assays in a population-based cohort of triple-negative breast cancer patients in the context of their clinically established scoring algorithms

BACKGROUND

Immunohistochemical (IHC) PD-L1 expression is commonly employed as predictive biomarker for checkpoint inhibitors in triple-negative breast cancer (TNBC). However, IHC evaluation methods are non-uniform and further studies are needed to optimize clinical utility.

METHODS

We compared the concordance, prognostic value and gene expression between PD-L1 IHC expression by SP142 immune cell (IC) score and 22C3 combined positive score (CPS; companion IHC diagnostic assays for atezolizumab and pembrolizumab, respectively) in a population-based cohort of 232 early-stage TNBC patients.

RESULTS

The expression rates of PD-L1 for SP142 IC ≥ 1%, 22C3 CPS ≥ 10, 22C3 CPS ≥ 1 and 22C3 IC ≥ 1% were 50.9%, 27.2%, 53.9% and 41.8%, respectively. The analytical concordance (kappa values) between SP142 IC+ and these three different 22C3 scorings were 73.7% (0.48, weak agreement), 81.5% (0.63) and 86.6% (0.73), respectively. The SP142 assay was better at identifying 22C3 positive tumors than the 22C3 assay was at detecting SP142 positive tumors. PD-L1 (CD274) gene expression (mRNA) showed a strong positive association with all two-categorical IHC scorings of the PD-L1 expression, irrespective of antibody and cut-off (Spearman Rho ranged from 0.59 to 0.62; all p-values < 0.001). PD-L1 IHC positivity and abundance of tumor infiltrating lymphocytes were of positive prognostic value in univariable regression analyses in patients treated with (neo)adjuvant chemotherapy, where it was strongest for 22C3 CPS ≥ 10 and distant relapse-free interval (HR = 0.18, p = 0.019). However, PD-L1 status was not independently prognostic when adjusting for abundance of tumor infiltrating lymphocytes in multivariable analyses.

CONCLUSION

Our findings support that the SP142 and 22C3 IHC assays, with their respective clinically applied scoring algorithms, are not analytically equivalent where they identify partially non-overlapping subpopulations of TNBC patients and cannot be substituted with one another regarding PD-L1 detection. Trial registration The Swedish Cancerome Analysis Network - Breast (SCAN-B) study, retrospectively registered 2nd Dec 2014 at ClinicalTrials.gov; ID NCT02306096.

A randomized double-blind trial of TQB2450 with or without anlotinib in pretreated driver-negative non-small cell lung cancer

OBJECTIVE

Immune monotherapy as second-line treatment confers only modest survival benefit on non-small cell lung cancer (NSCLC) patients with no mutated driver genes, necessitating combination treatment strategies. This phase Ib trial investigated the efficacy and safety of anti-PD-L1 antibody TQB2450 plus antiangiogenic drug anlotinib for NSCLC.

MATERIALS AND METHODS

Pretreated stage IIIB or IV NSCLC patients with wild-type EGFR/ALK and minimally one measurable lesion were randomized 1:1:1 to receive TQB2450 1200 mg plus placebo, or TQB2450 1200 mg plus anlotinib 10 or 12 mg. The primary outcome was progression-free survival (PFS) and the secondary outcomes included objective response rate (ORR).

RESULTS

Thirty-three patients received TQB2450 plus placebo and 34 patients each received TQB2450 plus anlotinib 10 mg and 12 mg. At the data cutoff, the median PFS was 8.7 months (95% CI 6.1-17.1) in the TQB2450 plus anlotinib group and 2.8 months (95% CI 1.4-4.7) in the TQB2450 only group. The ORR reached 30.9% (95% CI 20.2%-43.3%) in the TQB2450 plus anlotinib group and was 3.0% (95% CI 0.1%-15.8%) in the TQB2450 only group. In patients with PD-L1 ≥ 1%, the ORR was 50.0% (95% CI 33.4%-66.6%) for TQB2450 plus anlotinib and 5.3% (95% CI 0.1%-26.0%) for TQB2450 plus placebo. No new safety signals were observed.

CONCLUSION

Anlotinib plus TQB2450 demonstrated promising antitumor activities in advanced NSCLC patients without EGFR and ALK alterations and the toxicities were overall manageable. The study findings support the continued development of TQB2450 plus anlotinib for advanced NSCLC patients without driver gene alterations.

Monocyte subsets associated with the efficacy of anti‑PD‑1 antibody monotherapy

Immune checkpoint inhibitors (ICIs) are among the most notable advances in cancer immunotherapy; however, reliable biomarkers for the efficacy of ICIs are yet to be reported. Programmed death (PD)-ligand 1 (L1)-expressing CD14+ monocytes are associated with shorter overall survival (OS) time in patients with cancer treated with anti-PD-1 antibodies. The present study focused on the classification of monocytes into three subsets: Classical, intermediate and non-classical. A total of 44 patients with different types of cancer treated with anti-PD-1 monotherapy (pembrolizumab or nivolumab) were enrolled in the present study. The percentage of each monocyte subset was investigated, and the percentage of cells expressing PD-L1 or PD-1 within each of the three subsets was further analyzed. Higher pretreatment classical monocyte percentages were correlated with shorter OS (r=-0.32; P=0.032), whereas higher non-classical monocyte percentages were correlated with a favorable OS (r=0.39; P=0.0083). PD-L1-expressing classical monocytes accounted for a higher percentage of the total monocytes than non-classical monocytes with PD-L1 expression. In patients with non-small cell lung cancer (NSCLC), a higher percentage of PD-L1-expressing classical monocytes was correlated with shorter OS (r=-0.60; P=0.012), which is similar to the observation for the whole patient cohort. Comparatively, higher percentages of non-classical monocytes expressing PD-L1 were significantly associated with better OS, especially in patients with NSCLC (r=0.60; P=0.010). Moreover, a higher percentage of non-classical monocytes contributed to prolonged progression-free survival in patients with NSCLC (r=0.50; P=0.042), with similar results for PD-L1-expressing non-classical monocytes. The results suggested that the percentage of monocyte subsets in patients with cancer before anti-PD-1 monotherapy may predict the treatment efficacy and prognosis. Furthermore, more classical monocytes and fewer non-classical monocytes, especially those expressing PD-L1, are involved in shortening OS time, which may indicate the poor efficiency of anti-PD-1 treatment approaches.

Immune Biomarkers in Triple-Negative Breast Cancer: Improving the Predictivity of Current Testing Methods

Triple-negative breast cancer (TNBC) poses a significant challenge in terms of prognosis and disease recurrence. The limited treatment options and the development of resistance to chemotherapy make it particularly difficult to manage these patients. However, recent research has been shifting its focus towards biomarker-based approaches for TNBC, with a particular emphasis on the tumor immune landscape. Immune biomarkers in TNBC are now a subject of great interest due to the presence of tumor-infiltrating lymphocytes (TILs) in these tumors. This characteristic often coincides with the presence of PD-L1 expression on both neoplastic cells and immune cells within the tumor microenvironment. Furthermore, a subset of TNBC harbor mismatch repair deficient (dMMR) TNBC, which is frequently accompanied by microsatellite instability (MSI). All of these immune biomarkers hold actionable potential for guiding patient selection in immunotherapy. To fully capitalize on these opportunities, the identification of additional or complementary biomarkers and the implementation of highly customized testing strategies are of paramount importance in TNBC. In this regard, this article aims to provide an overview of the current state of the art in immune-related biomarkers for TNBC. Specifically, it focuses on the various testing methodologies available and sheds light on the immediate future perspectives for patient selection. By delving into the advancements made in understanding the immune landscape of TNBC, this study aims to contribute to the growing body of knowledge in the field. The ultimate goal is to pave the way for the development of more personalized testing strategies, ultimately improving outcomes for TNBC patients.

Biomarkers for Predicting Anti-Programmed Cell Death-1 Antibody Treatment Effects in Head and Neck Cancer

In recurrent or metastatic head and neck squamous cell carcinoma (R/M-HNSCC), survival outcomes are significantly better in patients who receive anti-programmed cell death-1 (PD-1) monoclonal antibody therapy than in those who receive standard therapy. However, there is no established biomarker that can predict the anti-PD-1 antibody treatment effect and immune-related adverse events (irAEs) in these patients. This study investigated the inflammatory and nutritional status in 42 patients with R/M-HNSCC and programmed cell death ligand-1 (PD-L1) polymorphisms (rs4143815 and rs2282055) in 35 of the 42 patients. The 1- and 2-year overall survival was 59.5% and 28.6%, respectively; the 1- and 2-year first progression-free survival was 19.0% and 9.5%, respectively, and the respective second progression-free survival was 50% and 27.8%. Performance status and inflammatory and nutritional status (assessed by the geriatric nutritional risk index, modified Glasgow prognostic score, and prognostic nutritional index) were identified as significant indicators of survival outcomes in multivariate analysis. Patients with ancestral alleles in PD-L1 polymorphisms had less frequent irAEs. Performance status and inflammatory and nutritional status before treatment were closely related to survival outcomes after PD-1 therapy. These indicators can be calculated using routine laboratory data. PD-L1 polymorphisms may be biomarkers for predicting irAEs in patients receiving anti-PD-1 therapy.

Inter- and Intra-Observer Agreement of PD-L1 SP142 Scoring in Breast Carcinoma-A Large Multi-Institutional International Study

The assessment of PD-L1 expression in TNBC is a prerequisite for selecting patients for immunotherapy. The accurate assessment of PD-L1 is pivotal, but the data suggest poor reproducibility. A total of 100 core biopsies were stained using the VENTANA Roche SP142 assay, scanned and scored by 12 pathologists. Absolute agreement, consensus scoring, Cohen's Kappa and intraclass correlation coefficient (ICC) were assessed. A second scoring round after a washout period to assess intra-observer agreement was carried out. Absolute agreement occurred in 52% and 60% of cases in the first and second round, respectively. Overall agreement was substantial (Kappa 0.654-0.655) and higher for expert pathologists, particularly on scoring TNBC (6.00 vs. 0.568 in the second round). The intra-observer agreement was substantial to almost perfect (Kappa: 0.667-0.956), regardless of PD-L1 scoring experience. The expert scorers were more concordant in evaluating staining percentage compared with the non-experienced scorers (R² = 0.920 vs. 0.890). Discordance predominantly occurred in low-expressing cases around the 1% value. Some technical reasons contributed to the discordance. The study shows reassuringly strong inter- and intra-observer concordance among pathologists in PD-L1 scoring. A proportion of low-expressors remain challenging to assess, and these would benefit from addressing the technical issues, testing a different sample and/or referring for expert opinions.

Genomic and Glycolytic Entropy Are Reliable Radiogenomic Heterogeneity Biomarkers for Non-Small Cell Lung Cancer

Radiogenomic heterogeneity features in ¹⁸F-fluorodeoxyglucose positron emission tomography (¹⁸F-FDG PET) have become popular in non-small cell lung cancer (NSCLC) research. However, the reliabilities of genomic heterogeneity features and of PET-based glycolytic features in different image matrix sizes have yet to be thoroughly tested. We conducted a prospective study with 46 NSCLC patients to assess the intra-class correlation coefficient (ICC) of different genomic heterogeneity features. We also tested the ICC of PET-based heterogeneity features from different image matrix sizes. The association of radiogenomic features with clinical data was also examined. The entropy-based genomic heterogeneity feature (ICC = 0.736) is more reliable than the median-based feature (ICC = -0.416). The PET-based glycolytic entropy was insensitive to image matrix size change (ICC = 0.958) and remained reliable in tumors with a metabolic volume of <10 mL (ICC = 0.894). The glycolytic entropy is also significantly associated with advanced cancer stages (p = 0.011). We conclude that the entropy-based radiogenomic features are reliable and may serve as ideal biomarkers for research and further clinical use for NSCLC.

Predictive biomarkers in gastric cancer

Predictive biomarkers are the mainstay of precision medicine. This review summarizes the advancements in tissue-based diagnostic biomarkers for gastric cancer, which is considered the leading cause of cancer-related deaths worldwide. A disease seen in the elderly, it is often diagnosed at an advanced stage, thereby limiting therapeutic options. In Western countries, neoadjuvant/perioperative (radio-)chemotherapy is administered, and adjuvant chemotherapy is administered in the East. The morpho-molecular classification of gastric cancer has opened novel avenues identifying Epstein-Barr-Virus (EBV)-positive, microsatellite instable, genomically stable and chromosomal instable gastric cancers. In chromosomal instable tumors, receptor tyrosine kinases (RKTs) (e.g., EGFR, FGFR2, HER2, and MET) are frequently overexpressed. Gastric cancers such as microsatellite instable and EBV-positive types often express immune checkpoint molecules, such as PD-L1 and VISTA. Genomically stable tumors show alterations in claudin 18.2. Next-generation sequencing is increasingly being used to search for druggable targets in advanced palliative settings. However, most tissue-based biomarkers of gastric cancer carry the risk of a sampling error due to intratumoral heterogeneity, and adequate tissue sampling is of paramount importance.

Loss of SATB2 expression correlates with cytokeratin 7 and PD-L1 tumor cell positivity and aggressiveness in colorectal cancer

Colorectal carcinoma (CRC) is a disease that causes significant morbidity and mortality worldwide. To improve treatment, new biomarkers are needed to allow better patient risk stratification in terms of prognosis. This study aimed to clarify the prognostic significance of colonic-specific transcription factor special AT-rich sequence-binding protein 2 (SATB2), cytoskeletal protein cytokeratin 7 (CK7), and immune checkpoint molecule programmed death-ligand 1 (PD-L1). We analyzed a cohort of 285 patients with surgically treated CRC for quantitative associations among the three markers and five traditional prognostic indicators (i.e., tumor stage, histological grade, variant morphology, laterality, and mismatch-repair/MMR status). The results showed that loss of SATB2 expression had significant negative prognostic implications relative to overall survival (OS) and cancer-specific survival (CSS), significantly shortened 5 years OS and CSS and 10 years CSS in patients with CRC expressing CK7, and borderline insignificantly shortened OS in patients with PD-L1 + CRC. PD-L1 showed a significant negative impact in cases with strong expression (membranous staining in 50-100% of tumor cells). Loss of SATB2 was associated with CK7 expression, advanced tumor stage, mucinous or signet ring cell morphology, high grade, right-sided localization but was borderline insignificant relative to PD-L1 expression. CK7 expression was associated with high grade and SATB2 loss. Additionally, a separate analysis of 248 neoadjuvant therapy-naïve cases was performed with mostly similar results. The loss of SATB2 and CK7 expression were significant negative predictors in the multivariate analysis adjusted for associated parameters and patient age. In summary, loss of SATB2 expression and gain of CK7 and strong PD-L1 expression characterize an aggressive phenotype of CRC.

Immune Checkpoint Inhibitors and Other Immune Therapies in Breast Cancer: A New Paradigm for Prolonged Adjuvant Immunotherapy

Background: Breast cancer is the most common form of cancer in women worldwide. Advances in the early diagnosis and treatment of cancer in the last decade have progressively decreased the cancer mortality rate, and in recent years, immunotherapy has emerged as a relevant tool against cancer. HER2+ and triple-negative breast cancers (TNBCs) are considered more immunogenic and suitable for this kind of treatment due to the higher rate of tumor-infiltrating lymphocytes (TILs) and programmed death ligand 1 (PD-L1) expression. In TNBC, genetic aberrations further favor immunogenicity due to more neo-antigens in cancer cells. Methods: This review summarizes the principal ongoing conventional and investigational immunotherapies in breast cancer. Particularly, immune checkpoint inhibitors (ICIs) and their use alone or combined with DNA damage repair inhibitors (DDRis) are described. Then, the issue on immunotherapy with monoclonal antibodies against HER-2 family receptors is updated. Other investigational immunotherapies include a new schedule based on the interferon beta-interleukin-2 sequence that was given in ER+ metastatic breast cancer patients concomitant with anti-estrogen therapy, which surprisingly showed promising results. Results: Based on the scientific literature and our own findings, the current evaluation of tumor immunogenicity and the conventional model of adjuvant chemotherapy (CT) are questioned. Conclusions: A novel strategy based on additional prolonged adjuvant immunotherapy combined with hormone therapy or alternated with CT is proposed.

Immune-Based Therapy in Triple-Negative Breast Cancer: From Molecular Biology to Clinical Practice

Triple-negative breast cancer (TNBC) has been considered for many years an orphan disease in terms of therapeutic options, with conventional chemotherapy (CT) still representing the mainstay of treatment in the majority of patients. Although breast cancer (BC) has been historically considered a "cold tumor", exciting progress in the genomic field leading to the characterization of the molecular portrait and the immune profile of TNBC has opened the door to novel therapeutic strategies, including Immune Checkpoint Inhibitors (ICIs), Poly ADP-Ribose Polymerase (PARP) inhibitors and Antibody Drug Conjugates (ADCs). In particular, compared to standard CT, the immune-based approach has been demonstrated to improve progression-free survival (PFS) and overall survival (OS) in metastatic PD-L1-positive TNBC and the pathological complete response rate in the early setting, regardless of PD-L1 expression. To date, PD-L1 has been widely used as a predictor of the response to ICIs; however, many patients do not benefit from the addition of immunotherapy. Therefore, PD-L1 is not a reliable predictive biomarker of the response, and its accuracy remains controversial due to the lack of a consensus about the assay, the antibody, and the scoring system to adopt, as well as the spatial and temporal heterogeneity of the PD-L1 status. In the precision medicine era, there is an urgent need to identify more sensitive biomarkers in the BC immune oncology field other than just PD-L1 expression. Through the characterization of the tumor microenvironment (TME), the analysis of peripheral blood and the evaluation of immune gene signatures, novel potential biomarkers have been explored, such as the Tumor Mutational Burden (TMB), Microsatellite Instability/Mismatch Repair Deficiency (MSI/dMMR) status, genomic and epigenomic alterations and tumor-infiltrating lymphocytes (TILs). This review aims to summarize the recent knowledge on BC immunograms and on the biomarkers proposed to support ICI-based therapy in TNBC, as well as to provide an overview of the potential strategies to enhance the immune response in order to overcome the mechanisms of resistance.