Prognostic value of tumor mutation burden and the relationship between tumor mutation burden and immune infiltration in HER2+ breast cancer: a gene expression-based study

Prognostic analysis of patients with breast cancer based on tumor mutational burden and DNA damage repair genes

Background

Breast cancer has a high tumor-specific death rate and poor prognosis. In this study, we aimed to provide a basis for the prognostic risk in patients with breast cancer using significant gene sets selected by analyzing tumor mutational burden (TMB) and DNA damage repair (DDR).

Methods

Breast cancer genomic and transcriptomic data were obtained from The Cancer Genome Atlas (TCGA). Breast cancer samples were dichotomized into high- and low-TMB groups according to TMB values. Differentially expressed DDR genes between high- and low-TMB groups were incorporated into univariate and multivariate cox regression model to build prognosis model. Performance of the prognosis model was validated in an independently new GEO dataset and evaluated by time-dependent ROC curves.

Results

Between high- and low-TMB groups, there were 6,424 differentially expressed genes, including 67 DDR genes. Ten genes associated with prognosis were selected by univariate cox regression analysis, among which seven genes constituted a panel to predict breast cancer prognosis. The seven-gene prognostic model, as well as the gene copy numbers are closely associated with tumor-infiltrating immune cells.

Conclusion

We established a seven-gene prognostic model comprising MDC1, PARP3, PSMB1, PSMB9, PSMD2, PSMD7, and PSMD14 genes, which provides a basis for further exploration of a population-based prediction of prognosis and immunotherapy response in patients with breast cancer.

Immune repertoire and responses to neoadjuvant TCHP therapy in HER2-positive breast cancer

Background

Despite the introduction of trastuzumab, pathologic complete response (pCR) is not attained in approximately 30-40% of Human epithelial growth factor receptor-2-positive breast cancer. Tumor-infiltrating lymphocytes (TIL) have been suggested as a predictive marker of treatment response, albeit not always effective. We investigated the relationship between trastuzumab, docetaxel, carboplatin, and pertuzumab (TCHP) treatment and immune repertoire as a treatment response predictor.

Design

In all, 35 cases were divided into two experimental groups: 10 and 25 cases in the preliminary and main experiments, respectively. In the preliminary experiment, the biopsy tissues before TCHP treatment and the surgical tissues after TCHP treatment were compared. In the main experiment, the biopsy tissues before TCHP treatment were compared according to the TCHP treatment response.

Methods

The T-cell repertoire for TRA, TRB, TRG, and TRD, and B-cell repertoire for immunoglobulin heavy, immunoglobulin kappa, and immunoglobulin lambda were evaluated. Whole transcriptome sequencing was also performed.

Results

In the preliminary experiment, the density and richness of the T-cell receptor (TCR) and B-cell receptor (BCR) repertoires decreased after treatment, regardless of TCHP response. In the main experiment, the Shannon's entropy index, density, and length of CDR3 of the TCR and BCR repertoires did not differ significantly in patients who did and did not achieve pCR. The pCR and non-pCR subgroups according to the level of TILs revealed that the non-pCR/lowTIL group had a higher proportion of low-frequency clones than the pCR/lowTIL group in TRA (non-pCR/lowTIL versus pCR/lowTIL, 0.01-0.1%, 63% versus 45.3%; <0.01%, 32.9% versus 51.8%, p < 0.001) and TRB (non-pCR/lowTIL versus pCR/lowTIL, 0.01-0.1%, 26.5% versus 14.7%; <0.01%, 72.0% versus 84.1%, p < 0.001).

Conclusions

The role of the diversity, richness, and density of the TCR and BCR repertoires as predictive markers for TCHP response was not identified. Compositions of low-frequency clones could be candidates for predictive factors of TCHP response; however, validation studies and further research are necessary.

The prognostic role of tumor mutation burden on survival of breast cancer: a systematic review and meta-analysis

Background

As a potential genetic biomarker, tumor mutation burden (TMB) has made progress in numerous tumors. There are limited data regarding TMB and its prognostic role is controversial in breast cancer. This systematic review and meta-analysis were conducted to assess the prognostic value of TMB on survival of breast cancer.

Methods

The databases PubMed, Embase, Web of Science, and Cochrane Library were searched for articles published through May 31, 2022. Moreover, effective data were extracted from included studies and calculated pooled effects of hazard ratio (HR) for overall survival (OS) and progression-free survival (PFS) by STATA 16.0. Heterogeneity was conducted by the I² statistic and p-value. Using publication bias evaluation, sensitivity analysis, and subgroup analysis, the origin of heterogeneity was further investigated.

Results

They were up to 1,722 patients collected from sixteen cohorts for this analysis. The pooled effects of HR for both OS (HR: 1.14, 95% CI: 0.83,1.58, p > 0.01) and PFS (HR: 0.96, 95% CI: 0.53,1.71, p > 0.01) indicated no statistically significant difference in the high TMB and low TMB group. In immune checkpoint inhibitors (ICIs) subgroup, high TMB patients demonstrated benefit of OS (HR: 0.72, 95% CI: 0.59,0.87, p = 0.001) and PFS (HR: 0.52, 95% CI: 0.35,0.77, p < 0.001), whereas difference was not statistically significant in the non-ICIs subgroup (OS, HR:1.76, 95% CI: 0.97,3.20, p = 0.062; PFS, HR:2.31, 95% CI: 0.89,5.97, p = 0.086). In addition, sensitivity analysis revealed that the pooled effects were stable. The funnel plot and Begg's test suggested the absence of publication bias.

Conclusion

Meta-analysis revealed that the prognostic relevance of TMB in breast cancer is limited in scope. High TMB may be associated with longer survival only in ICIs-based treatment, but the association is not evident in non-ICIs-based treatment.

Trial registration

[https://www.crd.york.ac.uk/PROSPERO], Prospective Register of Systematic Reviews (PROSPERO), identifier: CRD42022342488.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-10284-1.