Association of microsatellite instability (MSI) status with the 5-year outcome and genetic ancestry in a large Brazilian cohort of colorectal cancer

Implementation of the ProMisE classifier and validation of its prognostic impact in Brazilian endometrial carcinomas

Purpose

Molecular classification of endometrial cancer (EC) has emerged as a key approach to individualize therapy and define prognostic outcomes. This study aimed to implement the traditional ProMisE classification in a Brazilian population, compared with a molecular setting of ProMisE biomarkers, and evaluate its impact on patients' prognosis.

Patient and methods

A prospective cohort of 114 patients with primary EC treated at Barretos Cancer Hospital (BCH) between October 2020 and December 2022 was conducted. Pathology diagnosis, staging, treatment, and follow-up data were collected. The traditional ProMisE methodology was carried out by POLE hotspot sequencing and immunohistochemistry (IHC) for p53 and mismatch repair (MMR) proteins. We further evaluate the MMR and TP53 status by molecular approach, namely microsatellite instability (MSI) by PCR-based and TP53 mutation analysis by next-generation sequencing (NGS). The results of the 4 molecular groups in both methodologies were compared regarding agreement accuracy and survival outcomes.

Results

Among the 114 cases, the traditional ProMisE groups were: POLEmut 15.8%, MMRd 28.1%, p53abn 27.2%, and no specific molecular profile (NSMP) 28.9%. Considering the molecular classification approach, we observed a POLEmut group of 15.8%, MSI group of 23.7%, TP53 mutation of 27.2%, and NSMP of 33.3%. The concordance rate of both approaches was 86.8% (99/114 cases) with an overall accuracy of 0.87. Importantly, both traditional and molecular ProMisE approaches were associated with significant distinct overall survival (OS) and progression-free survival (PFS) outcomes, with POLEmut patients exhibiting a better prognosis (93.8% OS, at 24 months), whereas the p53abn having a worse survival time (68.9% of OS, at 24 months).

Conclusion

We reported for the first time the Brazilian profile of the ProMisE classification of endometrial cancer and demonstrated the prognostic impact of the traditional and molecular ProMisE classification on patient outcomes.

A CT-based deep learning for segmenting tumors and predicting microsatellite instability in patients with colorectal cancers: a multicenter cohort study

PURPOSE

To develop and validate deep learning (DL) models using preoperative contrast-enhanced CT images for tumor auto-segmentation and microsatellite instability (MSI) prediction in colorectal cancer (CRC).

MATERIALS AND METHODS

Patients with CRC who underwent surgery or biopsy between January 2018 and April 2023 were retrospectively enrolled. Mismatch repair protein expression was determined via immunohistochemistry or fluorescence multiplex polymerase chain reaction-capillary electrophoresis. Manually delineated tumor contours using arterial and venous phase CT images by three abdominal radiologists are served as ground truth. Tumor auto-segmentation used nnU-Net. MSI prediction employed ViT or convolutional neural networks models, trained and validated with arterial and venous phase images (image model) or combined clinical-pathological factors (combined model). The segmentation model was evaluated using patch coverage ratio, Dice coefficient, recall, precision, and F1-score. The predictive models' efficacy was assessed using areas under the curves and decision curve analysis.

RESULTS

Overall, 2180 patients (median age: 61 years ± 17 [SD]; 1285 males) were divided into training (n = 1159), validation (n = 289), and independent external test (n = 732) groups. High-level MSI status was present in 435 patients (20%). In the external test set, the segmentation model performed well in the arterial phase, with patch coverage ratio, Dice coefficient, recall, precision, and F1-score values of 0.87, 0.71, 0.72, 0.74, and 0.71, respectively. For MSI prediction, the combined models outperformed the clinical model (AUC = 0.83 and 0.82 vs 0.67, p < 0.001) and two image models (AUC = 0.75 and 0.77, p < 0.001). Decision curve analysis confirmed the higher net benefit of the combined model compared to the other models across probability thresholds ranging from 0.1 to 0.45.

CONCLUSION

DL enhances tumor segmentation efficiency and, when integrated with contrast-enhanced CT and clinicopathological factors, exhibits good diagnostic performance in predicting MSI in CRC.

Pan-tumor validation of a NGS fraction-based MSI analysis as a predictor of response to Pembrolizumab

Microsatellite instability high (MSI-H) and mismatch repair deficient (dMMR) tumor status have been demonstrated to predict patient response to immunotherapies. We developed and validated a next-generation sequencing (NGS)-based companion diagnostic (CDx) to detect MSI-H solid tumors via a comprehensive genomic profiling (CGP) assay, FoundationOne®CDx (F1CDx). To determine MSI status, F1CDx calculates the fraction of unstable microsatellite loci across >2000 loci using a fraction-based (FB) analysis. Across solid tumor types, F1CDx demonstrated a high analytical concordance with both PCR (n = 264) and IHC (n = 279) with an overall percent agreement (OPA) of 97.7% and 97.8%, respectively. As part of a retrospective bridging clinical study from KEYNOTE-158 Cohort K and KEYNOTE-164, patients with MSI-H tumors as determined by F1CDx demonstrated an objective response rate (ORR) of 43.0% to pembrolizumab. In real-world cancer patients from a deidentified clinicogenomic database, F1CDx was at least equivalent in assessing clinical outcome following immunotherapy compared with MMR IHC. Demonstrated analytical and clinical performance of F1CDx led to the pan-tumor FDA approval in 2022 of F1CDx to identify MSI-H solid tumor patients for treatment with pembrolizumab. F1CDx is an accurate, reliable, and FDA-approved method for the identification of MSI-H tumors for treatment with pembrolizumab.

Immune-checkpoint gene expression and BCG response in non-muscle invasive bladder cancer

METHODS

One-hundred-six patients diagnosed with non-muscle invasive bladder cancer and treated with intravesical BCG were included and divided into two groups, BCG-responsive (n = 47) and -unresponsive (n = 59). Immunohistochemistry was used to evaluate PD-L1 expression and MSI was assessed by a commercial multiplex PCR kit. The mRNA expression profile of 15 immune checkpoints was performed using the nCounter technology. For in silico validation, two distinct cohorts sourced from the Gene Expression Omnibus (GEO) database were used.

RESULTS

Among the 106 patients, only one (<1 %) exhibited MSI instability. PD-L1 expression was present in 9.4 % of cases, and no association was found with BCG-responsive status. We found low gene expression of canonic actionable immune checkpoints PDCD1 (PD-1), CD274 (PD-L1), and CTLA4, while high expression was observed for CD276 (B7-H3), CD47, TNFRSF14, IDO1 and PVR (CD155) genes. High IDO1 expression levels was associated with worst overall survival. The PDCD1, CTLA4 and TNFRSF14 expression levels were associated with BCG responsiveness, whereas TIGIT and CD276 were associated with unresponsiveness. Finally, CD276 was validated in silico cohorts.

CONCLUSION

In NMIBC, MSI is rare and PD-L1 expression is present in a small subset of cases. Expression levels of PDCD1, CTLA4, TNFRSF14, TIGIT and CD276 could constitute predictive biomarkers of BCG responsiveness.

A pan-cancer analysis of the core pre-mRNA 3' end processing factors, and their association with prognosis, tumor microenvironment, and potential targets

Alternative polyadenylation (APA) is a crucial mechanism for regulating gene expression during pre-mRNA 3' processing. Pre-mRNA 3' end processing factors is the main factor involved in this process. However, pre-mRNA 3' end processing factors in different cancer expression profiles and the relationship between pre-mRNA 3' end processing factors and tumor microenvironment and the prognosis of the same patient is still unclear. In this study, we conducted a comprehensive exploration of the core pre-mRNA 3' end processing factors across various cancer types by utilizing common cancer database, and revealing a robust correlation between the expression of these core factors and tumor characteristics. Leveraging advanced bioinformatics databases, we evaluated the expression levels and prognostic relevance of pre-mRNA 3' end processing factors across pan-cancer tissues. Our extensive pan-cancer analysis revealed unique expression patterns of pre-mRNA 3' end processing factors in both tumor and adjacent non-tumorous tissues. Notably, we found a significant correlation between the expression levels of pre-mRNA 3' end processing factors and patient prognosis. Furthermore, we identified strong associations between pre-mRNA 3' end processing factors expression and various factors, such as stromal, immune, RNA stemness, and DNA stemness scores across pan-cancer tissues. Our data also highlighted a link between the expression of pre-mRNA 3' end processing factors and sensitivity to specific drugs, including pyrazoloacndine, amonaflide, and chelerythrinede, among others. We found four key pre-mRNA 3' end processing factors that play a crucial role in mRNA preprocessing. Our study illuminates the potential promotion and inhibition role of pre-mRNA 3' end processing regulators in the progression of cancer, CPSF2, CPSF3, CSTF2, SYMPK offering valuable insights for future research investigations on these regulators as diagnostic markers and therapeutic targets across pan-cancer.

Establishment and molecular characterization of HCB-541, a novel and aggressive human cutaneous squamous cell carcinoma cell line

Cutaneous squamous cell carcinoma (cSCC) is a common type of skin cancer that can result in significant morbidity, although it is usually well-managed and rarely metastasizes. However, the lack of commercially available cSCC cell lines hinders our understanding of this disease. This study aims to establish and characterize a new metastatic cSCC cell line derived from a Brazilian patient. A tumor biopsy was taken from a metastatic cSCC patient, immortalized, and named HCB-541 after several passages. The cytokeratin expression profile, karyotypic alterations, mutational analysis, mRNA and protein differential expression, tumorigenic capacity in xenograft models, and drug sensitivity were analyzed. The HCB-541 cell line showed a doubling time between 20 and 30 h and high tumorigenic capacity in the xenograft mouse model. The HCB-541 cell line showed hypodiploid and hypotetraploidy populations. We found pathogenic mutations in TP53 p.(Arg248Leu), HRAS (Gln61His) and TERT promoter (C228T) and high-level microsatellite instability (MSI-H) in both tumor and cell line. We observed 37 cancer-related genes differentially expressed when compared with HACAT control cells. The HCB-541 cells exhibited high phosphorylated levels of EGFR, AXL, Tie, FGFR, and ROR2, and high sensitivity to cisplatin, carboplatin, and EGFR inhibitors. Our study successfully established HCB-541, a new cSCC cell line that could be useful as a valuable biological model for understanding the biology and therapy of metastatic skin cancer.

Ancestry and self-reported race in Brazilian breast cancer women

OBJECTIVE

This study aimed to evaluate the association between self-reported race/color and ancestry in Brazilian patients with breast cancer.

METHODS

This was an observational, transversal, epidemiological study, evaluating race and ancestry in 1,127 patients with breast cancer. For genetic ancestry, a 46-AIM-INDEL panel was used. The ancestral profile was evaluated with the Structure v.2.3.3 software. Descriptive statistics were performed. To assess differences between race and ancestry, an analysis of variance with Bonferoni adjustment was used.

RESULTS

The race distribution was 77.7% white, 17.6% brown, 4.1% black, 0.4% yellow, and 0.3% cafuse. The African ancestry proportion was significantly (p<0.001) more evident in black [0.63±0.21 (0.17-0.96)], followed by brown [0.25±0.16 (0.02-0.70)], and less frequent in white skin color. The European ancestry proportion was significantly (p<0.001) higher in white [0.72±0.17 (0.02-0.97)], followed by brown [0.57±0.19 (0.12-0.92)], yellow [0.27±0.31 (0.12-0.620], and black [0.24±0.19 (0.02-0.72)]. The Asiatic ancestry proportion is significantly (p<0.001) higher in yellow [0.48±0.51 (0.04-0.93)]. The Amerindian ancestry proportion frequency was the least frequent in all groups, and cafuse patients did not express differences between all race groups. The brown race group presented differences in African and European ancestry.

CONCLUSION

Although we found many similarities between white European ancestry, black African ancestry, and yellow Asian ancestry, there is great miscegenation between patients. Although they can be labeled as having one race, they do present many ancestral genes that would allow their inclusion in another race group.

Biomarkers for Immune Checkpoint Inhibitor Response in NSCLC: Current Developments and Applicability

Lung cancer has the highest mortality rate among all cancer types, resulting in over 1.8 million deaths annually. Immunotherapy utilizing immune checkpoint inhibitors (ICIs) has revolutionized the treatment of non-small cell lung cancer (NSCLC). ICIs, predominantly monoclonal antibodies, modulate co-stimulatory and co-inhibitory signals crucial for maintaining immune tolerance. Despite significant therapeutic advancements in NSCLC, patients still face challenges such as disease progression, recurrence, and high mortality rates. Therefore, there is a need for predictive biomarkers that can guide lung cancer treatment strategies. Currently, programmed death-ligand 1 (PD-L1) expression is the only established biomarker for predicting ICI response. However, its accuracy and robustness are not consistently reliable. This review provides an overview of potential biomarkers currently under development or in the validation stage that hold promise in improving the classification of responders and non-responders to ICI therapy in the near future.

Digital expression profile of immune checkpoint genes in medulloblastomas identifies CD24 and CD276 as putative immunotherapy targets

Introduction

Medulloblastoma is the most common and lethal pediatric malignant brain tumor. It comprises four main molecular subgroups: WNT-activated, SHH-activated, Group 3, and Group 4. Medulloblastoma treatment is surgical resection, craniospinal radiation, and chemotherapy. However, many patients do not respond to therapy, and most suffer severe side effects. Cancer immunotherapy targeting immune checkpoints (IC) (PD-1, PD-L1, and CTLA4) has been getting disappointing outcomes in brain tumors. Nevertheless, other less explored immune checkpoints may be promising candidates for medulloblastoma therapy.

Objectives

In the present study, we aimed to characterize the expression profile of 19 immune checkpoints in medulloblastoma.

Methods

We analyzed 88 formalin-fixed paraffin-embedded medulloblastomas previously classified for each molecular subgroup and three non-tumoral brain tissue. mRNA levels of 19 immune checkpoint-related genes were quantified using the nCounter (PanCancer Immune Profiling Panel) assay. Further in silico analysis was performed in two larger public microarray datasets, one of which enabled comparisons between tumoral and non-tumoral tissues. Immunohistochemistry of PD-L1 was performed in a subset of cases. Microsatellite instability was also molecularly analyzed.

Results

We observed an absence of expression of the canonic ICs, namely PDCD1 (PD-1), CD274 (PD-L1), and CTLA4, as well as CD80, CD86, BTLA, IDO1, CD48, TNFSF14, CD160, CEACAM1, and CD244. PD-L1 protein expression was also practically absent. We found higher mRNA levels of CD24, CD47, CD276 (B7-H3), and PVR, and lower mRNA levels of HAVCR2, LAG3, and TIGIT genes, with significant differences across the four molecular subgroups. Compared to the non-tumor tissues, the expression levels of CD276 in all subgroups and CD24 in SHH, Group 3, and Group 4 subgroups are significantly higher. The in silico analysis confirmed the expression profile found in the Brazilian cohort, including the lower/absent expression of the canonic ICs. Moreover, it confirmed the overexpression of CD24 and CD276 in medulloblastomas compared with the non-tumor tissue. Additionally, CD276 and CD24 high levels were associated with worse survival.

Conclusion

These results highlight the low or absence of mRNA levels of the canonic targetable ICs in medulloblastomas. Importantly, the analysis revealed overexpression of CD24 and CD276, which can constitute prognostic biomarkers and attractive immunotherapy targets for medulloblastomas.

Cutaneous and acral melanoma cross-OMICs reveals prognostic cancer drivers associated with pathobiology and ultraviolet exposure

Ultraviolet radiation (UV) is causally linked to cutaneous melanoma, yet the underlying epigenetic mechanisms, known as molecular sensors of exposure, have not been characterized in clinical biospecimens. Here, we integrate clinical, epigenome (DNA methylome), genome and transcriptome profiling of 112 cutaneous melanoma from two multi-ethnic cohorts. We identify UV-related alterations in regulatory regions and immunological pathways, with multi-OMICs cancer driver potential affecting patient survival. TAPBP, the top gene, is critically involved in immune function and encompasses several UV-altered methylation sites that were validated by targeted sequencing, providing cost-effective opportunities for clinical application. The DNA methylome also reveals non UV-related aberrations underlying pathological differences between the cutaneous and 17 acral melanomas. Unsupervised epigenomic mapping demonstrated that non UV-mutant cutaneous melanoma more closely resembles acral rather than UV-exposed cutaneous melanoma, with the latter showing better patient prognosis than the other two forms. These gene-environment interactions reveal translationally impactful mechanisms in melanomagenesis.