Subpopulation Treatment Effect Pattern Plot (STEPP) analysis of Ki67 assay according to histology: prognostic relevance for resected early stage 'pure' and 'mixed' lobular breast cancer

Histological Aspects and Quantitative Assessment of Ki67 as Prognostic Factors in Breast Cancer Patients: Result from a Single-Center, Cross Sectional Study

Background and objectives: Our aim is to explore the relationship between the levels of protein encoded by Ki67 and the histopathological aspects regarding the overall survival and progression-free survival in a single university center. A secondary objective was to examine other factors that can influence these endpoints. New approaches to the prognostic assessment of breast cancer have come from molecular profiling studies. Ki67 is a nuclear protein associated with cell proliferation. Together with the histological type and tumor grade, it is used to appreciate the aggressiveness of the breast tumors. Materials and Methods: We conducted a retrospective single-institution study, at Elias University Emergency Hospital, Bucharest, Romania, in which we enrolled women with stage I to III breast cancer. The protocol was amended to include the immunohistochemistry determination of Ki67 and the histological aspects. The methodology consisted in using a Kaplan-Meier analysis for the entire sample and restricted mean survival time up to 36 months. Results: Both lower Ki67 and low tumor grade are associated with better prognosis in terms of overall survival (OS) and progression-free survival (PFS) for our patients' cohort. In our group, the histological type did not impact the time to progression or survival. Conclusions: Both overall survival and progression-free survival may be influenced by the higher value of Ki67 and less differentiated tumors. Further studies are needed in order to establish if the histologic type may impact breast cancer prognostic, probably together with other histologic and molecular markers.

Targeted next-generation sequencing identifies genomic abnormalities potentially driving the prognosis of early-stage invasive lobular breast carcinoma patients stratified according to a validated clinico-pathological model

Introduction

The clinico-pathological and molecular factors that drive the prognosis of invasive lobular breast carcinoma (ILC) are not entirely explored. In this regard, the development and validation of a prognostic model for ILC and the investigation of the distribution of molecular abnormalities (focusing on CDK4/6 alterations) according to prognosis were the aims of this study.

Patients and methods

Two clinico-pathological multi-center data-sets of early-stage ILC patients (Training/Validation Set, TS/VS) were gathered. A 3-class model was developed according to the multivariate analysis for disease-free-survival (DFS) and externally validated. Mutational, copy number variation and transcriptomic analyses by targeted next generation sequencing (NGS) were performed (and validated with quantitative PCR) in an explorative cohort of patients with poor and good prognosis.

Results

Data from overall 773 patients (TS/VS: 491/282) were gathered. The developed model significantly discriminated low/intermediate/high risk in the TS (10-years DFS: 76.3%/67.6%/39.8%, respectively, p<0.0001) and in the VS (p<0.0001). In the explorative cohort for molecular analysis (34 patients), CDK4 gain was present exclusively in the poor prognosis group (35.0%, p = 0.03; OR 7.98, 95%CI 1.51–42.1, p = 0.014). Moreover, CDK4 and 6 overexpression showed a trend toward an association with poor prognosis (OR 2.7, 95%CI 0.4–18.1, p = 0.3; OR 3.29, 95%CI 0.56–19.25, p = 0.18).

Conclusions

A risk stratification model, able to accurately separate early-stage ILC patients’ prognosis into different risk classes according to clinico-pathological variables, allowed to investigate potential biomarkers of prognosis with targeted NGS. CDK4 gain is suggested for future validation as a prognostic biomarker and a potential therapeutic opportunity in ILC patients.

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The current multicenter analysis developed and validated a prognostic nomogram for early stage ILC.

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A next-generation sequencing analysis was performed in prognostic ‘outlier’ patients.

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CDK4 gain emerges as a potential negative prognostic factor in ILC patients. .

Long noncoding RNA PVT1 inhibits renal cancer cell apoptosis by up-regulating Mcl-1

Long non-coding RNA plasmacytoma variant translocation 1 (PVT1) is up-regulated in various human cancers, and our results indicated that PVT1 was up-regulated in clear cell renal cell carcinoma tissues. The Cancer Genome Atlas cohort analysis revealed that in clear cell renal cell carcinoma, higher PVT1 expression correlated with advanced TNM stage, histological grade, and poor survival. PVT1 knockdown promoted apoptosis, inhibited renal cancer cell proliferation, decreased Mcl-1, and increased cleaved caspase-3 and cleaved PARP. PVT1 increased Mcl-1 mRNA levels in renal cancer cells by promoting mRNA stability without influencing its transcription. in vitro, the enhanced apoptosis arising from PVT1 suppression was attenuated by overexpressing Mcl-1. In addition, in vivo experiments showed that PVT1 knockdown repressed xenograft tumor growth, while Mcl-1 overexpression partially rescued xenograft tumor growth. These results indicate the PVT1/Mcl-1 pathway inhibits renal cancer cell apoptosis in vitro and in vivo. PVT1 may thus serve as a novel biomarker, and the PVT1/Mcl-1 pathway may be a useful therapeutic target for clear cell renal cell carcinoma.

Prognostic impact of proliferation for resected early stage 'pure' invasive lobular breast cancer: Cut-off analysis of Ki67 according to histology and clinical validation

INTRODUCTION

The intent of this analysis was to investigate and validate the prognostic potential of Ki67 in a multi-center series of patients affected by early stage 'pure' invasive lobular carcinoma (ILC).

METHODS

Clinical-pathological data of patients affected by ILC were correlated with overall survival and disease-free survival (OS/DFS); data from a parallel invasive ductal carcinoma (IDC) patients' cohort were gathered as well. The maximally selected Log-Rank statistics analysis was applied to Ki67 continuous variable to estimate the appropriate cut-off. The Subpopulation Treatment Effect Pattern Plot (STEPP) analysis was performed as well.

RESULTS

Data from overall 1097 (457/222 ILC: training/validation set; 418 IDC) patients were gathered. The identified optimal Ki67 cut-offs were 4% and 14% for DFS in ILC and IDC cohort, respectively. In ILC patients, the Ki67 cut-off was an independent OS predictor. Ten-years OS and DFS were 89.9% and 77.2% (p = 0.007) and 79.4% and 69.2% (p = 0.03) for patients with Ki67 ≤ 4% and >4%, respectively. In IDC patients, 10-years OS was 93.8% and 71.7%, p = 0.02, DFS was 84.0% and 52.6%, p = 0.0003, for patients with Ki67 ≤ 14% and >14%, respectively. In the validation set, the optimal Ki67 OS cut-off was 5%. The STEPP analysis showed that in the presence of low Ki67 values, IDC patients have a better DFS than ILC patients, while with the increase of values the prognosis tends to overlap.

CONCLUSIONS

Despite the retrospective design of the study, the prognostic relevance of Ki67 (as well as its optimal cut-off) seems to significantly differ according to breast cancer histology.