Prediction of survival after neoadjuvant chemotherapy for breast cancer by evaluation of tumor-infiltrating lymphocytes and residual cancer burden

Tumor-infiltrating lymphocytes as a predictor of axillary and primary tumor pathological response after neoadjuvant chemotherapy in patients with breast cancer: a retrospective cohort study

PURPOSE

Tumor-infiltrating lymphocytes (TILs) can predict complete pathological response (pCR) of tumor in the breast but not so well-defined in the axilla after neoadjuvant chemotherapy. Since axillary surgery is being increasingly de-escalated after NACT, we aimed to investigate the relationship between TILs and pCR in the axilla and breast, as well as survival amongst NACT patients.

METHODS

Clinicopathological data on patients who underwent NACT between 2013 and 2020 were retrospectively examined. Specifically, pre-TILs (before NACT), post-TILs (after NACT) and ΔTIL (changes in TILs) were assessed. Primary endpoint was pCR and secondary endpoints were breast cancer-free interval (BCFI) and overall survival (OS).

RESULTS

Two hundred and twenty patients with nodal metastases were included. Overall axillary and breast pCR rates were 42.7% (94/220) and 39.1% (86/220), respectively, whereas the combined pCR rate was 32.7% (72/220). High pre-TILs (OR 2.03, 95% CI 1.02-4.05; p = 0.04) predicted axillary pCR whereas, high post-TILs (OR 0.33, 95% CI 0.14-0.76; p = 0.009) and increased ΔTILs (OR 0.25, 95% CI 0.08-0.79; p = 0.02) predicted non-axillary pCR. TILs were not a significant predictor for BCFI and OS.

CONCLUSIONS

This study supports the potential use of pre-TILs to select initially node-positive patients for axillary surgical de-escalation after NACT.

Prognostic factors of patients with human epidermal growth factor receptor 2-positive breast cancer following neoadjuvant therapy: Development and validation of a predictive nomogram

OBJECTIVE

Human epidermal growth factor receptor 2 (HER2)-positive breast cancer exhibits an aggressive phenotype and poor prognosis. The application of neoadjuvant therapy (NAT) in patients with breast cancer can significantly reduce the risks of disease recurrence and improve survival. By integrating different clinicopathological factors, nomograms are valuable tools for prognosis prediction. This study aimed to assess the prognostic value of clinicopathological factors in patients with HER2-positive breast cancer and construct a nomogram for outcome prediction.

METHODS

We retrospectively analyzed the clinicopathological data from 374 patients with breast cancer admitted to the Fourth Hospital of Hebei Medical University between January 2009 and December 2017, who were diagnosed with invasive breast cancer through preoperative core needle biopsy pathology, underwent surgical resection after NAT, and were HER2-positive. Patients were randomly divided into a training and validation set at a ratio of 7:3. Univariate and multivariate survival analyses were performed using Kaplan-Meier and Cox proportional hazards regression models. Results of the multivariate analysis were used to create nomograms predicting 3-, 5-, and 8-year overall survival (OS) rates. Calibration curves were plotted to test concordance between the predicted and actual risks. Harrell C-index and time-dependent receiver operating characteristic (ROC) curves were used to evaluate the discriminability of the nomogram prediction model.

RESULTS

All included patients were women, with a mean age of 50 ± 10.4 years (range: 26-72 years). In the training set, both univariate and multivariate analyses identified residual cancer burden (RCB) class, tumor-infiltrating lymphocytes(TILs), and clinical stage as independent prognostic factors for OS, and these factors were combined to construct a nomogram. The calibration curves demonstrated good concordance between the predicted and actual risks, and the C-index of the nomogram was 0.882 (95 % CI 0.863-0.901). The 3-, 5-, and 8-year areas under the ROC curve (AUCs) were 0.909, 0.893, and 0.918, respectively, indicating good accuracy of the nomogram. The calibration curves also demonstrated good concordance in the validation set, with a C-index of 0.850 (95 % CI 0.804-0.896) and 3-, 5-, and 8-year AUCs of 0.909, 0.815, and 0.834, respectively, which also indicated good accuracy.

CONCLUSION

The nomogram prediction model accurately predicted the prognostic status of post-NAT patients with breast cancer and was more accurate than clinical stage and RCB class. Therefore, it can serve as a reliable guide for selecting clinical treatment measures for breast cancer.

Prognostic stratification ability of the CPS+EG scoring system in HER2-low and HER2-zero early breast cancer treated with neoadjuvant chemotherapy

BACKGROUND

The CPS+EG scoring system was initially described in unselected early breast cancer (eBC) patients treated with neoadjuvant chemotherapy (NAC), leading to refined prognostic stratification, and thus helping to select patients for additional post-NAC treatments. It remains unknown whether the performance is the same in new biological breast cancer entities such as the HER2-low subtype.

PATIENTS AND METHODS

Outcomes (disease-free (DFS) and overall survival OS)) of 608 patients with HER2-non amplified eBC and treated with NAC were retrospectively analyzed according to CPS-EG score. We compared the prognostic stratification abilities of the CPS+EG in HER2-low and HER2-0 eBC, analyzing ER+ and ER- tumors separately.

RESULTS

In ER+ eBC, the CPS+EG scoring system seems to retain a prognostic value, both in HER2-low and HER2-0 tumors, by distinguishing populations with significantly different outcomes (good: score 0-1, poor: score 2-3, and very poor: score 4-5). Using C-indices for DFS and OS, CPS+EG provided the highest prognostic information in ER+ eBC, especially in HER2-0 tumors. In contrast, in ER- eBC, the CPS+EG does not appear to be able to distinguish different outcome groups, either in HER2-low or HER2-0 tumors. In ER- eBC, C-indices for DFS and OS were highest for pathological stage, reflecting the predominant prognostic importance of residual disease in this subtype.

CONCLUSIONS

HER2-low status does not influence the prognostic performance of the CPS+EG score. Our results confirm the usefulness of the CPS+EG score in stratifying the prognosis of ER+ eBC after NAC, for both HER2-0 and HER2-low tumors. For ER- eBC, HER2-low status does not influence the performance of the CPS+EG score, which was lower than that of the pathological stage alone.

The residual cancer burden index as a valid prognostic indicator in breast cancer after neoadjuvant chemotherapy

PURPOSE

The residual cancer burden index (RCB) was proposed as a response evaluation criterion in breast cancer patients treated with Neoadjuvant Chemotherapy (NAC). This study evaluated the relevance of RCB with replase-free survival (RFS).

METHODS

The clinical data of 254 breast cancer patients who received NAC between 2016 and 2020 were retrospectively collected. The relationship between clinicopathologic factors and RFS was evaluated using Cox proportional hazards regression models. RFS estimates were determined by Kaplan-Meier(K-M) analysis and compared using the log-rank test. Multivariate logistic regression analysis was used to evaluate the risk factors associated with RCB. Receiver operating characteristic (ROC) curves showed the potential of the RCB and MP grading systems as biomarkers for RFS.

RESULTS

At a median follow-up of 52 months, 59 patients(23.23%) developed relapse. Multivariate Cox regression showed that older age (P = 0.022), high Pathologic T stage after NAC (P = 0.023) and a high RCB score(P = 0.003) were risk factors for relapse. The outcomes of the multivariate logistic analysis indicated that RCB 0 (pathologic complete response [pCR]) was associated with HER2-positive patients (P = 0.002) and triple-negative breast cancer (TNBC) patients (P = 0.013). In addition, the RCB and MP scoring systems served as prognostic markers for patients who received NAC, and their area under curves (AUCs) were 0.691 and 0.342, respectively.

CONCLUSION

These data suggest that RCB can be equally applied to predict RFS in Chinese patients with NAC. The application of RCB may help guide the selection of treatment strategies.

18F-FDG PET/CT-based deep learning radiomics predicts 5-years disease-free survival after failure to achieve pathologic complete response to neoadjuvant chemotherapy in breast cancer

BACKGROUND

This study aimed to assess whether a combined model incorporating radiomic and depth features extracted from PET/CT can predict disease-free survival (DFS) in patients who failed to achieve pathologic complete response (pCR) after neoadjuvant chemotherapy.

RESULTS

This study retrospectively included one hundred and five non-pCR patients. After a median follow-up of 71 months, 15 and 7 patients experienced recurrence and death, respectively. The primary tumor volume underwent feature extraction, yielding a total of 3644 radiomic features and 4096 depth features. The modeling procedure employed Cox regression for feature selection and utilized Cox proportional-hazards models to make predictions on DFS. Time-dependent receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were utilized to evaluate and compare the predictive performance of different models. 2 clinical features (RCB, cT), 4 radiomic features, and 7 depth features were significant predictors of DFS and were included to develop models. The integrated model incorporating RCB, cT, and radiomic and depth features extracted from PET/CT images exhibited the highest accuracy for predicting 5-year DFS in the training (AUC 0.943) and the validation cohort (AUC 0.938).

CONCLUSION

The integrated model combining radiomic and depth features extracted from PET/CT images can accurately predict 5-year DFS in non-pCR patients. It can help identify patients with a high risk of recurrence and strengthen adjuvant therapy to improve survival.

Analysis of neoadjuvant chemotherapy for breast cancer: a 20-year retrospective analysis of patients of a single institution

BACKGROUND

Neoadjuvant chemotherapy (NAC) has been widely applied in operable breast cancer patients. This study aim to identify the predictive factors of overall survival(OS) and recurrence free survival (RFS) in breast cancer patients who received NAC from a single Chinese institution.

PATIENTS AND METHODS

There were 646 patients recruited in this study. All the patients were treated at department of Surgical Oncology, Sir Run Run Shaw Hospital between February 25, 1999 and August 22, 2018. The relevant clinicopathological and follow-up data were collected retrospectively. RFS and OS were assessed using the Kaplan-Meier method. Multivariate Cox proportional hazards model was also employed. Multi-variate logistic regression model was simulated to predict pathologic complete response (pCR).

RESULTS

In total, 118 patients (18.2%) achieved pCR during NAC. The 5-year OS was 94.6% versus 78.1% in patients with and without pCR, respectively (P < 0.001). The 5-year RFS was 95.3% and 72.7%, respectively (P < 0.001). No difference was detected among molecular subtypes of 5-year RFS in patients obtained pCR. Factors independently predicting RFS were HER2-positive subtype (hazard ratio(HR), 1.906; P = 0.004), triple-negative breast cancer (TNBC) (HR,2.079; P = 0.003), lymph node positive after NAC(HR,2.939; P < 0.001), pCR (HR, 0.396;P = 0.010), and clinical stage III (HR,2.950; P = 0.016). Multi-variate logistic regression model was simulated to predict the pCR rate after NAC, according to clinical stage, molecular subtype, ki-67, LVSI, treatment period and histology. In the ROC curve analysis, the AUC of the nomogram was 0.734 (95%CI,0.867-12.867).

CONCLUSIONS

Following NAC, we found that pCR positively correlated with prognosis and the molecular subtype was a prognostic factor.

Proposing a novel molecular subtyping scheme for predicting distant recurrence-free survival in breast cancer post-neoadjuvant chemotherapy with close correlation to metabolism and senescence

Background

High relapse rates remain a clinical challenge in the management of breast cancer (BC), with distant recurrence being a major driver of patient deterioration. To optimize the surveillance regimen for distant recurrence after neoadjuvant chemotherapy (NAC), we conducted a comprehensive analysis using bioinformatics and machine learning approaches.

Materials and methods

Microarray data were retrieved from the GEO database, and differential expression analysis was performed with the R package 'Limma'. We used the Metascape tool for enrichment analyses, and 'WGCNA' was utilized to establish co-expression networks, selecting the soft threshold power with the 'pickSoftThreshold' algorithm. We integrated ten machine learning algorithms and 101 algorithm combinations to identify key genes associated with distant recurrence in BC. Unsupervised clustering was performed with the R package 'ConsensusCluster Plus'. To further screen the key gene signature of residual cancer burden (RCB), multiple knockdown studies were analyzed with the Genetic Perturbation Similarity Analysis (GPSA) database. Single-cell RNA sequencing (scRNA-seq) analysis was conducted through the Tumour Immune Single-cell Hub (TISCH) database, and the XSum algorithm was used to screen candidate small molecule drugs based on the Connectivity Map (CMAP) database. Molecular docking processes were conducted using Schrodinger software. GMT files containing gene sets associated with metabolism and senescence were obtained from GSEA MutSigDB database. The GSVA score for each gene set across diverse samples was computed using the ssGSEA function implemented in the GSVA package.

Results

Our analysis, which combined Limma, WGCNA, and machine learning approaches, identified 16 RCB-relevant gene signatures influencing distant recurrence-free survival (DRFS) in BC patients following NAC. We then screened GATA3 as the key gene signature of high RCB index using GPSA analysis. A novel molecular subtyping scheme was developed to divide patients into two clusters (C1 and C2) with different distant recurrence risks. This molecular subtyping scheme was found to be closely associated with tumor metabolism and cellular senescence. Patients in cluster C2 had a poorer DRFS than those in cluster C1 (HR: 4.04; 95% CI: 2.60-6.29; log-rank test p < 0.0001). High GATA3 expression, high levels of resting mast cell infiltration, and a high proportion of estrogen receptor (ER)-positive patients contributed to better DRFS in cluster C1. We established a nomogram based on the N stage, RCB class, and molecular subtyping. The ROC curve for 5-year DRFS showed excellent predictive value (AUC=0.91, 95% CI: 0.95-0.86), with a C-index of 0.85 (95% CI: 0.81-0.90). Entinostat was identified as a potential small molecule compound to reverse high RCB after NAC. We also provided a comprehensive review of the EDCs exposures that potentially impact the effectiveness of NAC among BC patients.

Conclusion

This study established a molecular classification scheme associated with tumor metabolism and cancer cell senescence to predict RCB and DRFS in BC patients after NAC. Furthermore, GATA3 was identified and validated as a key gene associated with BC recurrence.

Prognostic relevance of tumor‑infiltrating lymphocytes in residual tumor tissue from patients with triple‑negative breast cancer following neoadjuvant chemotherapy: A systematic review and meta‑analysis

Further adjuvant chemotherapy treatment can provide benefits to certain patients with triple-negative breast cancer (TNBC) that fail to achieve pathological complete response (pCR) after the administration of a neoadjuvant chemotherapy (NAC) regimen. However, biomarkers suitable for identifying patients likely to experience poor prognostic outcomes after undergoing additional adjuvant chemotherapy are currently lacking. Accordingly, the present meta-analysis was conducted to explore the relationship between tumor-infiltrating lymphocytes (TILs) or TIL subtypes (CD4+ or CD8+) in residual tumor (RT) tissue following NAC and TNBC patient prognosis. Relevant studies published through March 2023 were identified in Pubmed, The Cochrane Library, Embase and Web of Science databases. After excluding irrelevant studies, data were extracted from the remaining reports, while study quality was analyzed with the Newcastle-Ottawa Scale. Subsequent analyses were performed with Stata 14.0 and Review Manager 5.3. In total, seven relevant studies incorporating 1,202 patients were identified, all of which were retrospective cohort studies. Pooled analyses demonstrated that those patients exhibiting higher levels of RT TIL infiltration following NAC exhibited significantly improved recurrence-free, metastasis-free and event-free survival (RFS/MFS/EFS) compared with patients with lower RT TIL infiltration levels, together with an improved distant recurrence-free interval (DRFI) [hazard ratio (HR)=0.52; 95% confidence interval (CI)=0.39-0.69; P<0.00001]. In addition, patients exhibiting high RT TIL infiltration exhibited improved overall survival (OS) and breast cancer-specific survival (BCSS; HR=0.49; 95% CI=0.38-0.65; P<0.00001). Additional subgroup analyses revealed that patients with higher TIL infiltration levels or TIL subtype (CD4+ or CD8+) infiltration exhibited improved RFS/MFS/EFS/DRFI as compared with patients with lower levels of overall TIL or TIL subtype (CD4+ or CD8+) infiltration in RT tissue (HR=0.35, 95% CI=0.20-0.59, P<0.0001; HR=0.49, 95% CI=0.33-0.71, P=0.0002). Consistently, the OS/BCSS of patients exhibiting high levels of overall TIL or TIL subtype (CD4+ or CD8+) infiltration was increased compared with patients with lower levels of such infiltration (HR=0.33, 95% CI=0.19-0.59, P=0.0002; HR=0.55, 95% CI=0.41-0.76, P=0.0002). These data thus demonstrate that levels of overall TIL infiltration or infiltration by CD4+ or CD8+ TILs in RT following NAC can be used as a biomarker to reliably predict prognostic outcomes in patients with TNBC, in addition to highlighting possible targets that may guide the further immunotherapeutic management of these patients.

Tumor infiltrating lymphocytes and neutrophil-to-lymphocyte ratio in relation to pathological complete remission to neoadjuvant therapy and prognosis in triple negative breast cancer

OBJECTIVE

To explore the correlation between the peripheral blood neutrophil-to-lymphocyte ratio (NLR) and tumor infiltrating lymphocyte (TIL) before neoadjuvant therapy (NAT) and the prognosis of patients with triple negative breast cancer.

METHOD

A total of 126 patients with TNBC who received NAT were screened out. TILs, CD8+TIL and FOXP3+TIL were detected by immunohistochemistry in core needle biopsy specimens before treatment, and NLR was calculated. Kaplan-Meier analysis was used to estimate survival rates. Univariate and multivariate analyses were performed using Cox proportional hazards regression.

RESULTS

NLR was negatively correlated with TILs density (p = 0.040) and FOXP3+ TIL was positively correlated with NLR (p = 0.019). Patients with low NLR/high TILs density showed the highest pCR rate (46/48, 95 %), while only 6/22 patients (21 %) with high NLR/low TILs density achieved pCR. Multivariate analysis showed that high NLR was independently associated with pCR ((HR = 5.043, 95 %CI = 1.637-15.535, p = 0.005). High T stage, lymph node involvement, lymphovascular invasion, high NLR, low TILs density and low CD8+ TIL were associated with poor OS and BCSS. Multivariate Cox regression analysis showed that high NLR (HR = 36.182, 95 %CI = 4.120-317.759, p = 0.001), high CD8+ TIL density (HR = 0.182, 95 %CI = 0.044-0.754, p = 0.019) were independently associated with poor OS. Similarly, high NLR (HR = 23.989, 95 %CI = 2.275-252.131, p = 0.008) was independently associated with worse BCSS.

CONCLUSIONS

NLR may help to screen the high-risk population of TNBC patients after neoadjuvant therapy.

End-of-neoadjuvant treatment circulating microRNAs and HER2-positive breast cancer patient prognosis: An exploratory analysis from NeoALTTO

Background

The absence of breast cancer cells in surgical specimens, i.e., pathological complete response (pCR), is widely recognized as a favorable prognostic factor after neoadjuvant therapy. In contrast, the presence of disease at surgery characterizes a prognostically heterogeneous group of patients. Here, we challenged circulating microRNAs (miRNAs) at the end of neoadjuvant therapy as potential prognostic biomarkers in the NeoALTTO study.

Methods

Patients treated within the trastuzumab arm (i.e., pre-operative weekly trastuzumab for 6 weeks followed by the addition of weekly paclitaxel for 12 weeks; post-operative FEC for 3 cycles followed by trastuzumab up to complete 1 year of treatment) were randomized into a training (n= 54) and testing (n= 72) set. RT-PCR-based high-throughput miRNA profile was performed on plasma samples collected at the end of neoadjuvant treatment of both sets. After normalization, circulating miRNAs associated with event free survival (EFS) were identified by univariate and multivariate Cox regression model.

Results

Starting from 23 circulating miRNAs associated with EFS in the training set, we generated a 3-circulating miRNA prognostic signature consisting of miR-185-5p, miR-146a-5p, miR-22-3p, which was confirmed in the testing set. The 3-circulating miRNA signature showed a C-statistic of 0.62 (95% confidence interval [95%CI] 0.53-0.71) in the entire study cohort. By resorting to a multivariate Cox regression model we found a statistical significant interaction between the expression values of miR-194-5p and pCR status (p.interaction =0.005) with an estimate Hazard Ratio (HR) of 1.83 (95%CI 1.14- 2.95) in patients with pCR, and 0.87 (95%CI 0.69-1.10) in those without pCR. Notably, the model including this interaction along with the abovementioned 3-circulating miRNA signature provided the highest discriminatory capability with a C-statistic of 0.67 (95%CI 0.58-0.76).

Conclusions

Circulating miRNAs are informative to identify patients with different prognosis among those with heterogeneous response after trastuzumab-based neoadjuvant treatment, and may be an exploitable tool to select candidates for salvage adjuvant therapy.

Tumor Infiltrating Lymphocytes across Breast Cancer Subtypes: Current Issues for Biomarker Assessment

Tumor-infiltrating lymphocytes (TILs) represent a surrogate biomarker of anti-tumor, lymphocyte-mediated immunity. In early, triple-negative breast cancer, TILs have level 1B of evidence to predict clinical outcomes. TILs represent a promising biomarker to select patients who can experience a better prognosis with de-intensified cancer treatments and derive larger benefits from immune checkpoint inhibitors. However, the assessment and the validation of TILs as a biomarker require a prospective and rigorous demonstration of its clinical validity and utility, provided reproducible analytical performance. With pending data about the prospective validation of TILs' clinical validity to modulate treatments in early breast cancer, this review summarizes the most important current issues and future challenges related to the implementation of TILs assessments across all breast cancer subtypes and their potential integration into clinical practice.

The types of tumor infiltrating lymphocytes are valuable for the diagnosis and prognosis of breast cancer

This study aimed at constructing a diagnostic immune risk score (dIRS) system and a prognostic immune risk score (pIRS) system for diagnose and prognosis of breast cancer (BC). The gene expression data of BC were downloaded from TCGA dataset (training set), and from GSE65194, GSE29044, GSE42568, and GSE20685 (validation sets). Then, the immune cell type proportions in each dataset were assessed using EPIC tool, and the dIRS system was built based on the SVM-RFE and RF-VIMP algorithms. Subsequently, the pIRS system and the nomogram survival model were established separately using penalized and rms packages. Finally, the differential expressed genes (DEGs) between low and high pIRS groups were screened, and submitted for functional analysis. The dIRS system consisted of B cells, CD8 + T cells, endothelial cells, NK cells, and other cells had high accuracy in distinguishing BC patients from the healthy controls (AUROC &gt;0.7). Subsequently, the pIRS system with the five prognosis-associated immune-infiltrating cell was constructed, and Kaplan-Meier analysis demonstrated that the survival rate of low pIRS group was significantly higher than that of high pIRS group (p &lt; 0.05). Based on age, pathologic stage and the pIRS values, the nomogram survival model was built. The AUROC value, Specificity value, Sensitivity value and C-index of the nomogram survival model were higher than 0.7000, and had a good predictive ability for BC. Finally, a total of 539 DEGs were identified, and significantly enriched in six pathways. The dIRS system and the pIRS system composed of immune cells might be critical for the diagnosis and prognosis of BC patients.

The immune modifying effects of chemotherapy and advances in chemo-immunotherapy

Immune checkpoint inhibitors (ICIs) have transformed the treatment paradigm for several malignancies. While the use of single-agent or combined ICIs has achieved acceptable disease control rates in a variety of solid tumors, such approaches have yet to show substantial therapeutic efficacy in select difficult-to-treat cancer types. Recently, select chemotherapy regimens are emerging as extensive modifiers of the tumor microenvironment, leading to the reprogramming of local immune responses. Accordingly, data is now emerging to suggest that certain anti-neoplastic agents modulate various immune cell processes, most notably the cross-presentation of tumor antigens, leukocyte trafficking, and cytokine biosynthesis. As such, the combination of ICIs and cytotoxic chemotherapy are beginning to show promise in many cancers that have long been considered poorly responsive to ICI-based immunotherapy. Here, we discuss past and present attempts to advance chemo-immunotherapy in these difficult-to-treat cancer histologies, mechanisms through which select chemotherapies modify tumor immunogenicity, as well as important considerations when designing such approaches to maximize efficacy and improve therapeutic response rates.

Immune Checkpoint Blockade in Hormone Receptor-Positive Breast Cancer: Resistance Mechanisms and Future Perspectives

Anti-programmed cell death protein 1 immunotherapy has been incorporated in the treatment algorithm of triple-negative breast cancer (TNBC). However, clinical trial results for patients with hormone receptor (HR)-positive disease appear less compelling. HR-positive tumors exhibit lower levels of programmed death-ligand 1 expression in comparison with their triple-negative counterparts. Moreover, signaling through estrogen receptor alters the immune microenvironment, rendering such tumors immunologically "cold." To explain differential responses to immune checkpoint blockade, this review interrogates differences between HR-positive and TNBC. Starting from distinct genomic features, we further present disparities concerning the tumor microenvironment and finally, we summarize early-phase clinical trial results on promising novel immunotherapy combinations.

Microcalcifications and Peritumoral Edema Predict Survival Outcome in Luminal Breast Cancer Treated with Neoadjuvant Chemotherapy

Background Little is known regarding findings at imaging associated with survival in patients with luminal breast cancer treated with neoadjuvant chemotherapy (NAC). Purpose To determine the relationship between imaging (MRI, US, and mammography) and clinical-pathologic variables in predicting distant metastasis-free survival (DMFS) and overall survival (OS) in patients with luminal breast cancer treated with NAC. Materials and Methods In this retrospective study, consecutive women with luminal breast cancer who underwent NAC followed by surgery were identified from the breast cancer registries of two hospitals. Women from one hospital between January 2003 and July 2015 were classified into the development cohort, and women from the other hospital between January 2007 and July 2015 were classified into the validation cohort. MRI scans, US scans, and mammograms before and after NAC (hereafter, referred to as pre- and post-NAC, respectively) and clinical-pathologic data were reviewed. Peritumoral edema was defined as the water-like high signal intensity surrounding the tumor on T2-weighted MRI scans. The prediction model was developed in the development cohort by using Cox regression and then tested in the validation cohort. Results The development cohort consisted of 318 women (68 distant metastases, 54 deaths) and the validation cohort consisted of 165 women (37 distant metastases, 14 deaths) (median age, 46 years in both cohorts). Post-NAC MRI peritumoral edema, age younger than 40 years, clinical N2 or N3, and lymphovascular invasion were associated with worse DMFS (all, P < .05). Pre-NAC mammographic microcalcifications, post-NAC MRI peritumoral edema, age older than 60 years, and clinical T3 or T4 were associated with worse OS (all, P < .05). The prediction model showed good discrimination ability (C index, 0.67-0.75 for DMFS and 0.70-0.77 for OS) and stratified prognosis into low-risk and high-risk groups (10-year DMFS rates, 79% vs 21%, respectively; and 10-year OS rates, 95%-96% vs 63%-67%, respectively) in the validation cohort. Conclusion MRI features and clinical-pathologic variables were identified that were associated with prolonged survival of patients with luminal breast cancer treated with neoadjuvant chemotherapy. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Kataoka in this issue.

Differences in tumor-infiltrating lymphocyte density and prognostic factors for breast cancer by patient age

Background

Lymphocytes that surround cancer participate in tumor-related immune responses and are called tumor-infiltrating lymphocytes (TILs). Several recent reports suggest TILs index the tumor microenvironment and predict the therapeutic effect of chemotherapy. However, only few studies have studied the relationship between age and TILs. Aging reduces host immunity, and we predict that it may also affect TILs. Thus, we hypothesized that older breast cancer (BC) patients may have low TIL density than younger BC patients. Here, we retrospectively analyzed the differences in TILs by age and the therapeutic effects of preoperative chemotherapy (POC) in BC patients who were aged either less than 45 years or more than 60 years.

Methods

We retrospectively examined the data of 356 breast cancer patients who underwent POC, including 75 patients aged ≤ 45 years and 116 patients aged > 60 years. Using pre-treatment needle biopsy specimens, TIL density was compared for each age group by Student’s t-test. After analyzing different factors that affect TIL density, prognostic factors were also examined.

Results

Older patients with triple-negative BC had significantly lower TIL density than younger patients, while in human epidermal growth factor receptor 2 (HER2)-enriched BC, TIL density was significantly higher in the younger age group than that in the older age group. In addition, younger patients with HER2-rich breast cancer showed significantly higher complete pathological response rates than older patients with HER2-rich BC. In addition, significant differences in overall survival were observed among these patients with triple-negative BC.

Conclusions

Our study suggests that younger BC patients possess significantly higher TIL density than older patients. These differences may influence the therapeutic efficacy in highly immunogenic subtypes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12957-022-02513-5.

Persistence of ctDNA in Patients with Breast Cancer During Neoadjuvant Treatment Is a Significant Predictor of Poor Tumor Response

PURPOSE

Accurate response assessment during neoadjuvant systemic treatment (NST) poses a clinical challenge. Therefore, a minimally invasive assessment of tumor response based on cell-free circulating tumor DNA (ctDNA) may be beneficial to guide treatment decisions.

EXPERIMENTAL DESIGN

We profiled 93 genes in tissue from 193 patients with early breast cancer. Patient-specific assays were designed for 145 patients to track ctDNA during NST in plasma. ctDNA presence and levels were correlated with complete pathological response (pCR) and residual cancer burden (RCB) as well as clinicopathologic characteristics of the tumor to identify potential proxies for ctDNA release.

RESULTS

At baseline, ctDNA could be detected in 63/145 (43.4%) patients and persisted in 25/63 (39.7%) patients at mid-therapy (MT) and 15/63 (23.8%) patients at the end of treatment. ctDNA detection at MT was significantly associated with higher RCB (OR = 0.062; 95% CI, 0.01-0.48; P = 0.0077). Of 31 patients with detectable ctDNA at MT, 30 patients (96.8%) were nonresponders (RCB II, n = 8; RCB III, n = 22) and only one patient responded to the treatment (RCB I). Considering all 145 patients with baseline (BL) plasma, none of the patients with RCB 0 and only 6.7% of patients with RCB I had ctDNA detectable at MT, whereas 30.6% and 29.6% of patients with RCB II/III, respectively, had a positive ctDNA result.

CONCLUSIONS

Overall, our results demonstrate that the detection and persistence of ctDNA at MT may have the potential to negatively predict response to neoadjuvant treatment and identify patients who will not achieve pCR or be classified with RCB II/III.

Development and Validation of a Novel Model for Predicting Prognosis of Non-PCR Patients After Neoadjuvant Therapy for Breast Cancer

Purpose

Pathologic complete response (pCR) after neoadjuvant therapy is an important indicator of long-term prognosis and the primary endpoint of many neoadjuvant studies. For breast cancer patients who do not achieve pCR, prognostic indicators related to prognosis are particularly important. This study is constructing a prediction model with more accurate and reliable prediction results by combining multiple clinicopathological factors, so as to provide a more accurate decision-making basis for subsequent clinical treatment.

Patients and Methods

In this study, 1,009 cases of invasive breast cancer and surgically resected after neoadjuvant therapy from 2010 to 2017. All indicators in this trial were interpreted in a double-blind manner by two pathologists with at least 10 years of experience, including histological grading, Tils, ER, PR, HER2, and Ki67. The prediction model used R language to calculate the calibration degree and ROC curve of the prediction model in the training set and validation set.

Results

Through univariate survival analysis, the results showed histological grade (P=0.037), clinical stage (P<0.001), HER2 (P=0.044), RCB class (P<0.001), Tils (P<0.001), lymph node status (P =0.049), MP grade (P=0.013) are related to OS in non-PCR patients after neoadjuvant. Data were analyzed by substituting in a multivariate analysis, and the results were that clinical stage, HER2, RCB grading, and Tils grading were correlated with OS in non-PCR patients after neoadjuvant therapy for breast cancer. Among all cases in the training set, the prediction model predicted that the 3-year survival AUC value was 0.95 and 5-year survival AUC value was 0.79, and the RCB classification of 3-year survival and 5-year survival were 0.70 and 0.67, respectively, which proved that the prediction model could predict the OS of non-PCR patients after neoadjuvant therapy for breast cancer more accurately than the RCB classification, and showed the same results in HR, HER2+, and TN classifications. It also showed the same results in validation set.

Conclusion

These data indicate that the predicted values of the prediction model developed in this study match the actual survival rates without underestimating the mortality risk and have a relatively accurate prediction effect.

How the variability between computer-assisted analysis procedures evaluating immune markers can influence patients' outcome prediction

Differences between computer-assisted image analysis (CAI) algorithms may cause discrepancies in the identification of immunohistochemically stained immune biomarkers in biopsies of breast cancer patients. These discrepancies have implications for their association with disease outcome. This study aims to compare three CAI procedures (A, B and C) to measure positive marker areas in post-neoadjuvant chemotherapy biopsies of patients with triple-negative breast cancer (TNBC) and to explore the differences in their performance in determining the potential association with relapse in these patients. A total of 3304 digital images of biopsy tissue obtained from 118 TNBC patients were stained for seven immune markers using immunohistochemistry (CD4, CD8, FOXP3, CD21, CD1a, CD83, HLA-DR) and were analyzed with procedures A, B and C. The three methods measure the positive pixel markers in the total tissue areas. The extent of agreement between paired CAI procedures, a principal component analysis (PCA) and Cox multivariate analysis was assessed. Comparisons of paired procedures showed close agreement for most of the immune markers at low concentration. The probability of differences between the paired procedures B/C and B/A was generally higher than those observed in C/A. The principal component analysis, largely based on data from CD8, CD1a and HLA-DR, identified two groups of patients with a significantly lower probability of relapse than the others. The multivariate regression models showed similarities in the factors associated with relapse for procedures A and C, as opposed to those obtained with procedure B. General agreement among the results of CAI procedures would not guarantee that the same predictive breast cancer markers were consistently identified. These results highlight the importance of developing additional strategies to improve the sensitivity of CAI procedures.

Precision Medicine and Triple-Negative Breast Cancer: Current Landscape and Future Directions

Simple Summary

The implementation of precision medicine will revolutionize cancer treatment paradigms. Notably, this goal is not far from reality: genetically similar cancers can be treated similarly. The heterogeneous nature of triple-negative breast cancer (TNBC) made it a suitable candidate to practice precision medicine. Using TNBC molecular subtyping and genomic profiling, a precision medicine-based clinical trial is ongoing. This review summarizes the current landscape and future directions of precision medicine and TNBC.

Abstract

Triple-negative breast cancer (TNBC) is an aggressive and heterogeneous subtype of breast cancer associated with a high recurrence and metastasis rate that affects African-American women disproportionately. The recent approval of targeted therapies for small subgroups of TNBC patients by the US ‘Food and Drug Administration’ is a promising development. The advancement of next-generation sequencing, particularly somatic exome panels, has raised hopes for more individualized treatment plans. However, the use of precision medicine for TNBC is a work in progress. This review will discuss the potential benefits and challenges of precision medicine for TNBC. A recent clinical trial designed to target TNBC patients based on their subtype-specific classification shows promise. Yet, tumor heterogeneity and sub-clonal evolution in primary and metastatic TNBC remain a challenge for oncologists to design adaptive precision medicine-based treatment plans.

The Immunology of Hormone Receptor Positive Breast Cancer

Immune checkpoint blockade (ICB) has revolutionized the treatment of cancer patients. The main focus of ICB has been on reinvigorating the adaptive immune response, namely, activating cytotoxic T cells. ICB has demonstrated only modest benefit against advanced breast cancer, as breast tumors typically establish an immune suppressive tumor microenvironment (TME). Triple-negative breast cancer (TNBC) is associated with infiltration of tumor infiltrating lymphocytes (TILs) and patients with TNBC have shown clinical responses to ICB. In contrast, hormone receptor positive (HR+) breast cancer is characterized by low TIL infiltration and minimal response to ICB. Here we review how HR+ breast tumors establish a TME devoid of TILs, have low HLA class I expression, and recruit immune cells, other than T cells, which impact response to therapy. In addition, we review emerging technologies that have been employed to characterize components of the TME to reveal that tumor associated macrophages (TAMs) are abundant in HR+ cancer, are highly immune-suppressive, associated with tumor progression, chemotherapy and ICB-resistance, metastasis and poor survival. We reveal novel therapeutic targets and possible combinations with ICB to enhance anti-tumor immune responses, which may have great potential in HR+ breast cancer.

SOLTI-1805 TOT-HER3 Study Concept: A Window-of-Opportunity Trial of Patritumab Deruxtecan, a HER3 Directed Antibody Drug Conjugate, in Patients With Early Breast Cancer

Background: Preclinical data support a key role for the human epidermal growth factor receptor 3 (HER3) pathway in hormone receptor (HR)-positive breast cancer. Recently, new HER3 directed antibody drug conjugates have shown activity in breast cancer. Given the need to better understand the molecular biology, tumor microenvironment, and mechanisms of drug resistance in breast cancer, we designed this window-of-opportunity study with the HER3 directed antibody drug conjugate patritumab deruxtecan (HER3-DXd; U3-1402). Trial Design: Based on these data, a prospective, multicenter, single-arm, window-of-opportunity study was designed to evaluate the biological effect of patritumab deruxtecan in the treatment of naïve patients with HR-positive/HER2-negative early breast cancer whose primary tumors are ≥1 cm by ultrasound evaluation. Patients will be enrolled in four cohorts according to the mRNA-based ERBB3 expression by central assessment. The primary endpoint is a CelTIL score after one single dose. A translational research plan is also included to provide biological information and to evaluate secondary and exploratory objectives of the study. Trial Registration Number: EudraCT 2019-004964-23; NCT number: NCT04610528.

Determination of breast cancer prognosis after neoadjuvant chemotherapy: comparison of Residual Cancer Burden (RCB) and Neo-Bioscore

Background

To compare RCB (Residual Cancer Burden) and Neo-Bioscore in terms of prognostic performance and see if adding pathological variables improve these scores.

Methods

We analysed 750 female patients with invasive breast cancer (BC) treated with neoadjuvant chemotherapy (NAC) at Institut Curie between 2002 and 2012. Scores were compared in global population and by BC subtype using Akaike information criterion (AIC), C-Index (concordance index), calibration curves and after adding lymphovascular invasion (LVI) and pre-/post-NAC TILs levels.

Results

RCB and Neo-Bioscore were significantly associated to disease-free and overall survival in global population and for triple-negative BC. RCB had the lowest AICs in every BC subtype, corresponding to a better prognostic performance. In global population, C-Index values were poor for RCB (0.66; CI [0.61–0.71]) and fair for Neo-Bioscore (0.70; CI [0.65–0.75]). Scores were well calibrated in global population, but RCB yielded better prognostic performances in each BC subtype. Concordance between the two scores was poor. Adding LVI and TILs improved the performance of both scores.

Conclusions

Although RCB and Neo-Bioscore had similar prognostic performances, RCB showed better performance in BC subtypes, especially in luminal and TNBC. By generating fewer prognostic categories, RCB enables an easier use in everyday clinical practice.

A Decision-Making Supporting Prediction Method for Breast Cancer Neoadjuvant Chemotherapy

Neoadjuvant chemotherapy (NAC) may increase the resection rate of breast cancer and shows promising effects on patient prognosis. It has become a necessary treatment choice and is widely used in the clinical setting. Benefitting from the clinical information obtained during NAC treatment, computational methods can improve decision-making by evaluating and predicting treatment responses using a multidisciplinary approach, as there are no uniformly accepted protocols for all institutions for adopting different treatment regiments. In this study, 166 Chinese breast cancer cases were collected from patients who received NAC treatment at the First Bethune Hospital of Jilin University. The Miller–Payne grading system was used to evaluate the treatment response. Four machine learning multiple classifiers were constructed to predict the treatment response against the 26 features extracted from the patients’ clinical data, including Random Forest (RF) model, Convolution Neural Network (CNN) model, Support Vector Machine (SVM) model, and Logistic Regression (LR) model, where the RF model achieved the best performance using our data. To allow a more general application, the models were reconstructed using only six selected features, and the RF model achieved the highest performance with 54.26% accuracy. This work can efficiently guide optimal treatment planning for breast cancer patients.

The immunologic aspects in hormone receptor positive breast cancer

BACKGROUND

Although hormone receptor positive/HER2-negative (HR +/HER2-) breast cancer is the most diagnosed breast cancer type, the immunologic aspects HR positive breast cancer (BC) has been neglected until recently.  The purpose of this paper is to review the current knowledge of the immune environment in HR positive BC and the potential use of immunotherapy in these patients.

METHOD

A computer-based literature research was carried out using PubMed, American Society of Clinical Oncology Annual Meeting (ASCO) and San Antonio Breast Cancer Symposium (SABCS).

RESULTS

The tumour microenvironment (TME), with infiltrating immune cells, plays an important role in HR positive BC. However, the effects of these immune cells are different in the luminal cancers compared to the other breast cancer types. Even though PD-1 and PD-L1 are less expressed in HR positive BC, pathological complete response (pCR) was more often seen after PD-1 inhibitor treatment in patients with an increased expression. The studies support the assertion that endocrine therapy has immunomodulatory effect.

CONCLUSION

The reviewed literature indicates that immune cells play an important role in HR positive BC. Considerably more research is needed to determine the real effect of the TME in this patient group.

Perspectives on Triple-Negative Breast Cancer: Current Treatment Strategies, Unmet Needs, and Potential Targets for Future Therapies

Triple-negative breast cancer (TNBC), characterized by the absence or low expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor (HER2), is the most aggressive subtype of breast cancer. TNBC accounts for about 15% of breast cancer cases in the U.S., and is known for high relapse rates and poor overall survival (OS). Chemo-resistant TNBC is a genetically diverse, highly heterogeneous, and rapidly evolving disease that challenges our ability to individualize treatment for incomplete responders and relapsed patients. Currently, the frontline standard chemotherapy, composed of anthracyclines, alkylating agents, and taxanes, is commonly used to treat high-risk and locally advanced TNBC. Several FDA-approved drugs that target programmed cell death protein-1 (Keytruda) and programmed death ligand-1 (Tecentriq), poly ADP-ribose polymerase (PARP), and/or antibody drug conjugates (Trodelvy) have shown promise in improving clinical outcomes for a subset of TNBC. These inhibitors that target key genetic mutations and specific molecular signaling pathways that drive malignant tumor growth have been used as single agents and/or in combination with standard chemotherapy regimens. Here, we review the current TNBC treatment options, unmet clinical needs, and actionable drug targets, including epidermal growth factor (EGFR), vascular endothelial growth factor (VEGF), androgen receptor (AR), estrogen receptor beta (ERβ), phosphoinositide-3 kinase (PI3K), mammalian target of rapamycin (mTOR), and protein kinase B (PKB or AKT) activation in TNBC. Supported by strong evidence in developmental, evolutionary, and cancer biology, we propose that the K-RAS/SIAH pathway activation is a major tumor driver, and SIAH is a new drug target, a therapy-responsive prognostic biomarker, and a major tumor vulnerability in TNBC. Since persistent K-RAS/SIAH/EGFR pathway activation endows TNBC tumor cells with chemo-resistance, aggressive dissemination, and early relapse, we hope to design an anti-SIAH-centered anti-K-RAS/EGFR targeted therapy as a novel therapeutic strategy to control and eradicate incurable TNBC in the future.

Evaluation of the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer

Neoadjuvant chemotherapy is increasingly used in breast cancer, especially for downstaging the primary tumor in the breast and the metastatic axillary lymph node. Accurate evaluations of the response to neoadjuvant chemotherapy provide important information on the impact of systemic therapies on breast cancer biology, prognosis, and guidance for further therapy. Moreover, pathologic complete response is a validated and valuable surrogate prognostic factor of survival after therapy. Evaluations of neoadjuvant chemotherapy response are very important in clinical work and basic research. In this review, we will elaborate on evaluations of the efficacy of neoadjuvant chemotherapy in breast cancer and provide a clinical evaluation procedure for neoadjuvant chemotherapy.

Predictive and Prognostic Roles of Pathological Indicators for Patients with Breast Cancer on Neoadjuvant Chemotherapy

Currently, neoadjuvant chemotherapy is a standard therapeutic strategy for breast cancer, as it can provide timely and individualized chemo-sensitivity information and is beneficial for custom-designing subsequent treatment strategies. To accurately select candidates for neoadjuvant chemotherapy, the association between various immunohistochemical biomarkers of primary disease and tumor response to neoadjuvant chemotherapy has been investigated, and results have shown that certain pathological indicators evaluated after neoadjuvant chemotherapy are associated with long-term prognosis. The Food and Drug Administration (FDA) has recommended that complete pathological response can be used as a surrogate endpoint for neoadjuvant chemotherapy, which is related to better prognosis. Considering that residual tumor persists in the majority of patients after neoadjuvant chemotherapy, the value of various pathological indicators of residual disease in predicting the long-term outcomes is being extensively investigated. This review summarizes and compares various predictive and prognostic indicators for patients who have received neoadjuvant chemotherapy, and analyzes their efficacy in different breast cancer subtypes.

Residual cancer burden index and tumor-infiltrating lymphocyte subtypes in triple-negative breast cancer after neoadjuvant chemotherapy

PURPOSE

There is a need to refine the prognosis of triple-negative breast cancer (TNBC) patients after neoadjuvant chemotherapy (NAC) and to study the influence of the tumor microenvironment. We evaluated the prognostic value of pathological and immune markers in TNBC with residual disease (RD) after NAC.

METHODS

In a series of 186 TNBC patients treated by NAC, we assessed the prognostic value of the Residual Cancer Burden (RCB) index. In 109 patients with RD, we studied the impact of clinicopathological features and tumor immune response in the residual tumor on overall survival (OS) and distant recurrence-free interval (DRFI).

RESULTS

In the whole group, the OS and DRFI, at 3 years, were statistically different between the different classes of RCB (P = 0.0004 and P < 0.0001, respectively). In univariate analysis of the RD group, low RCB index and high ratios of stromal tumor-infiltrating lymphocytes (TILs), CD3 + TILs, CD4 + TILs, CD8 + TILs, and IDO1-positive cells were significant favorable prognostic factors for DRFI at 3 years. In the final multivariate model, CD4 + TILs and RCB index showed a statistically independent prognostic significance for DRFI [Hazard Ratio (HR) 2.88 (95%CI 1.34-6.17), P = 0.007 and HR 12.04 (95%CI 2.78-52.23, P < 0.0001), respectively]. The CD4 + TIL levels influenced survival in the different RCB classes with a significant effect observed in RCB-II and RCB-III classes (P = 0.05 and P = 0.05, respectively).

CONCLUSIONS

These results suggest that the combination of pathological (RCB index) and tumor micro-environmental features (CD4 + TILs) help refining the prognosis of TNBC patients with RD following NAC.

Can Tumor-Infiltrating Lymphocytes (TILs) Be a Predictive Factor for Lymph Nodes Status in Both Early Stage and Locally Advanced Breast Cancer?

The status of axillary lymph nodes is an important prognostic factor in the outcome of breast cancer tumors. New trials changed the attitude towards axillary clearance. In the era of development of new immune therapies for breast cancer, it is important to identify a biomarker that can predict lymph node status. Tumor-infiltrating lymphocytes (TILs) are a valuable indicator of the immune microenvironment that plays the central role in new anticancer drugs. Although the correlation between TILs and response to chemotherapy was established by previous studies, our retrospective study investigated the correlation between TILs and lymph node status. We analyzed data on 172 patients. According to stage, patients were divided in two groups: patients who underwent primary surgical treatment (breast-conserving or mastectomy and sentinel lymph node (SLN) biopsy +/− axillary clearance in conformity with lymph node status) and patients who received chemotherapy prior to surgical treatment (breast-conserving or mastectomy + axillary clearance). We showed a good inverse correlation between TILs and lymph nodes status for both early stage and locally advanced breast cancers. Moreover, TILs are a predictor for positive lymph nodes in the axilla in patients undergoing axillary clearance after SLN biopsy, with no statistical difference between the intrinsic or histological subtype of breast cancers. We also obtained a significant correlation between TILs and response to chemotherapy with no significative difference according to histological subtype. Although further data have still to be gathered before meeting the criteria for clinical utility, this study demonstrates that TILs are one of the most accredited forthcoming biomarkers for breast cancer (BC) patients.

Targeting immune cells for cancer therapy

Recent years have seen a renaissance in the research linking inflammation and cancer with immune cells playing a central role in smouldering inflammation in the tumor microenvironment. Diverse immune cell types infiltrate the tumor microenvironment, and the dynamic tumor-immune cell interplay gives rise to a rich milieu of cytokines and growth factors. Fundamentally, this intricate cross-talk creates the conducive condition for tumor cell proliferation, survival and metastasis. Interestingly, the prominent impact of immune cells is expounded in their contrary pro-tumoral role, as well as their potential anti-cancer cellular weaponry. The latter is known as immunotherapy, a concept born out of evidence that tumors are susceptible to immune defence and that by manipulating the immune system, tumor growth can be successfully restrained. Naturally, a deeper understanding of the multifaceted roles of various immune cell types thus contributes toward developing innovative anti-cancer strategies. Therefore, in this review we first outline the roles played by the major immune cell types, such as macrophages, neutrophils, natural killer cells, T cells and B cells. We then explain the recently-explored strategies of immunomodulation and discuss some important approaches via an immunology perspective.

Tumour infiltrating lymphocytes and PD-L1 expression as potential predictors of outcome in patients with malignant pleural mesothelioma

Malignant pleural mesothelioma (MPM) is a rare and aggressive form of tumour. Some mesotheliomas have been proven to be highly immunogenic. Here, we investigated the correlation between tumour infiltrating lymphocytes (TILs) or programmed cell death ligand 1 (PD-L1) expression with overall survival (OS) in patients with MPM. 62 Paraffin-embedded formalin fixed (PEFF) samples were analysed for TILs and PD-L1 expression. Patients were divided in 4 groups according to a cut-off of the percentage of TILs found per sample as measured by immunohistichemistry: "0" or absent (between 0 and 5%), "1" or low (between 6 and 25%), "2" or moderate (between 26 and 50%) and "3" or high (between 51 and 75%). OS was then correlated with different TILs' expression patterns. Moreover, PD-L1 expression was assessed within the tumour as well as in the adjacent stroma on the same samples. Higher expression of peritumoral TILs (Group 2 + 3) versus Group 0 and 1 correlated with improved OS (p-value = 0.02). On the contrary PD-L1 expression seemed to be inversely correlated with clinical outcomes, even in the absence of statistical significance (HR 1.76; p = 0.083 95% IC 0.92-3.36 in areas within the tumour; HR 1.60; p = 0.176 95%; IC 0.80-3.19 in areas within the stroma). No relationship between TILs and PD-L1 expression was identified. Our research supports the use of TILs and PD-L1 expression as potential outcome predictors in patients with MPM. The use of TILs and PD-L1 as biomarkers for checkpoint inhibitors' efficacy warrants future investigation.

Post-neoadjuvant treatment and the management of residual disease in breast cancer: state of the art and perspectives

Achieving a pathologic complete response after neoadjuvant treatment is associated with improved prognosis in breast cancer. The CREATE-X trial demonstrated a significant survival improvement with capecitabine in patients with residual invasive disease after neoadjuvant chemotherapy, and the KATHERINE trial showed a significant benefit of trastuzumab-emtansine (TDM1) in human epidermal growth factor receptor 2 (HER2)-positive patients who did not achieve a pathologic complete response after neoadjuvant treatment, creating interesting alternatives of post-neoadjuvant treatments for high-risk patients. New agents are arising as therapeutic options for metastatic breast cancer such as the cyclin-dependent kinase inhibitors and the immune-checkpoint inhibitors, but none has been incorporated into the post-neoadjuvant setting so far. Evolving techniques such as next-generation sequencing and gene expression profiles have improved our knowledge regarding the biology of residual disease, and also on the mechanisms involved in treatment resistance. The present manuscript reviews the current available strategies, the ongoing trials, the potential biomarker-guided approaches and the perspectives for the post-neoadjuvant treatment and the management of residual disease after neoadjuvant treatment in breast cancer.

Prognostic implications of residual disease tumor-infiltrating lymphocytes and residual cancer burden in triple-negative breast cancer patients after neoadjuvant chemotherapy

BACKGROUND

For primary triple-negative breast cancer (TNBC) treated with neoadjuvant chemotherapy (NAC), higher pretreatment tumor-infiltrating lymphocytes (TILs) correlates with increased pathologic complete response (pCR) rates, and improved survival. We evaluated the added prognostic value of residual disease (RD) TILs to residual cancer burden (RCB) in predicting survival post-NAC.

PATIENTS AND METHODS

We combined four TNBC NAC patient cohorts who did not achieve pCR. RD TILs were investigated for associations with recurrence-free survival (RFS), and overall survival (OS) using Cox models with stromal TILs as a continuous variable (per 10% increment). The likelihood ratio test was used to evaluate added prognostic value of RD TILs.

RESULTS

A total of 375 RD TNBC samples were evaluable for TILs and RCB. The median age was 50 years, with 62% receiving anthracycline/taxane chemotherapy. The RCB class after NAC was 11%, 50%, and 39% for I, II, and III, respectively. The median RD TIL level was 20% (IQR 10-40). There was a positive correlation between RD TIL levels and CD8+ T-cell density (ρ = 0.41). TIL levels were significantly lower with increasing post-NAC tumor (P = 0.005), nodal stage (P = 0.032), but did not differ by RCB class (P = 0.84). Higher RD TILs were significantly associated with improved RFS (HR: 0.86; 95% CI 0.79-0.92; P < 0.001), and improved OS (HR: 0.87; 95% CI 0.80-0.94; P < 0.001), and remained significant predictors in multivariate analysis (RFS P = 0.032; OS P = 0.038 for OS). RD TILs added significant prognostic value to multivariate models including RCB class (P < 0.001 for RFS; P = 0.021 for OS). The positive prognostic effect of RD TILs significantly differed by RCB class for RFS (PInt=0.003) and OS (PInt=0.008) with a greater magnitude of positive effect observed for RCB class II than class III.

CONCLUSIONS

TIL levels in TNBC RD are significantly associated with improved RFS and OS and add further prognostic information to RCB class, particularly in RCB class II.