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BACKGROUND: Copy number alterations (CNA) are acquired during the evolution of cancers from their early stage to metastatic stage. This study aims at analysing the clinical value of the identified metastasis-associated CNAs both in metastatic breast cancers (mBCs) and early breast cancers (eBCs). METHODS: Single-nucleotide polymorphism (SNP)-array was performed on 926 biopsies from mBC patients, enrolled in SAFIR02-BREAST prospective trial. CNA profiles of eBCs from The Cancer Genome Atlas Breast Invasive Carcinoma (n = 770), Molecular Taxonomy of Breast Cancer International Consortium (n = 1620) and PACS04 trial (n = 243) cohorts were used as references for comparing mBCs and eBCs CNA profiles. Overall survival was the considered survival endpoint. RESULTS: Among the twenty-one genes frequently altered in ER + /HER2- mBCs: focal amplification of TERT was associated with poor outcome in the ER + /HER2- mBC population. Among the ER + /HER2- mBCs patients for whom CDK4/6 inhibitors information before biopsies collection was available: we identified seven genes on post-treatment biopsies, including the cyclin-dependent kinase 4 (CDK4), which was amplified in 9.8% of the ER + /HER2- mBCs pretreated population, as compared to 1.5% in the ER + /HER2- mBCs unpretreated population (P = 2.82E-04) as well as the 3 eBC populations. CDK4 amplification was associated with poor outcome in the ER + /HER2- eBCs. CONCLUSIONS: This study provides insights into the biology of mBCs and identifies clinically useful genomic features for future improvement of breast cancer patient management.
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AIMS: Over 50% of breast cancer cases are "Human epidermal growth factor receptor 2 (HER2) low breast cancer (BC)", characterized by HER2 immunohistochemistry (IHC) scores of 1+ or 2+ alongside no amplification on fluorescence in situ hybridization (FISH) testing. The development of new anti-HER2 antibody-drug conjugates (ADCs) for treating HER2-low breast cancers illustrates the importance of accurately assessing HER2 status, particularly HER2-low breast cancer. In this study we evaluated the performance of a deep-learning (DL) model for the assessment of HER2, including an assessment of the causes of discordances of HER2-Null between a pathologist and the DL model. We specifically focussed on aligning the DL model rules with the ASCO/CAP guidelines, including stained cells' staining intensity and completeness of membrane staining. METHODS AND RESULTS: We trained a DL model on a multicentric cohort of breast cancer cases with HER2-IHC scores (n = 299). The model was validated on two independent multicentric validation cohorts (n = 369 and n = 92), with all cases reviewed by three senior breast pathologists. All cases underwent a thorough review by three senior breast pathologists, with the ground truth determined by a majority consensus on the final HER2 score among the pathologists. In total, 760 breast cancer cases were utilized throughout the training and validation phases of the study. The model's concordance with the ground truth (ICC = 0.77 [0.68-0.83]; Fisher P = 1.32e-10) is higher than the average agreement among the three senior pathologists (ICC = 0.45 [0.17-0.65]; Fisher P = 2e-3). In the two validation cohorts, the DL model identifies 95% [93% - 98%] and 97% [91% - 100%] of HER2-low and HER2-positive tumours, respectively. Discordant results were characterized by morphological features such as extended fibrosis, a high number of tumour-infiltrating lymphocytes, and necrosis, whilst some artefacts such as nonspecific background cytoplasmic stain in the cytoplasm of tumour cells also cause discrepancy. CONCLUSION: Deep learning can support pathologists' interpretation of difficult HER2-low cases. Morphological variables and some specific artefacts can cause discrepant HER2-scores between the pathologist and the DL model.
Sujet(s)
Marqueurs biologiques tumoraux , Tumeurs du sein , Apprentissage profond , Immunohistochimie , Récepteur ErbB-2 , Humains , Tumeurs du sein/anatomopathologie , Tumeurs du sein/diagnostic , Tumeurs du sein/métabolisme , Tumeurs du sein/génétique , Récepteur ErbB-2/métabolisme , Récepteur ErbB-2/génétique , Femelle , Marqueurs biologiques tumoraux/analyse , Marqueurs biologiques tumoraux/métabolisme , Anatomopathologistes , Hybridation fluorescente in situ , Adulte d'âge moyenRÉSUMÉ
BACKGROUND: Circadian rhythms regulate cellular physiology and could influence the efficacy of endocrine therapy (ET) in breast cancer (BC). We prospectively tested this hypothesis within the UNIRAD adjuvant phase III trial (NCT01805271). METHODS: 1278 patients with high-risk hormonal receptor positive (HR+)/HER2 negative (HER2-) primary BC were randomly assigned to adjuvant ET with placebo or everolimus. Patients prospectively reported in a diary the daily timing of ET intake among four 6-h slots (06:00-11:59 (morning), 12:00-17:59 (afternoon), 18:00-23:59 (evening), or 24:00-05:59 (nighttime). The association between ET timing and disease-free survival (DFS) was a prespecified secondary endpoint of the trial and the results of this observational study are reported here. FINDINGS: ET timing was recorded by 855 patients (67.2%). Patients declaring morning (n = 465, 54.4%) or afternoon (n = 45, 5.4%) ET intake were older than those declaring evening (n = 339, 39.6%) or nighttime (n = 5, 0.6%) intake. With a median follow-up of 46.7 months, 118 patients had a local (n = 30) or metastasis relapse (n = 84), and 41 patients died. ET intake timing was not associated with DFS in the whole population (HR = 0.77, 95% CI [0.53-1.12]). The association between ET intake timing and DFS according to the stratification factors revealed interactions with ET agent (tamoxifen versus Aromatase inhibitors (AI) with an increased DFS in the group of evening/nighttime versus morning/afternoon tamoxifen intake (HR = 0.43, 95% CI [0.22-0.85]), while no association was found for AI intake (HR = 1.07, 95% CI [0.68-1.69]). The interaction between ET intake timing and ET agent remained in multivariable analysis (HR = 0.38 [0.16-0.91]). INTERPRETATION: Tamoxifen intake in the evening/nighttime could be recommended in patients with high-risk HR+/HER2- BC while awaiting for results from further ET timing studies. FUNDING: UNIRAD was Supported by a grant from the French Ministry of Health PHRC 2012 and received funding from La Ligue contre le Cancer, Cancer Research-UK, Myriad Genetics, and Novartis.
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Tumeurs du sein , Adulte , Sujet âgé , Femelle , Humains , Adulte d'âge moyen , Antinéoplasiques hormonaux/usage thérapeutique , Antinéoplasiques hormonaux/administration et posologie , Protocoles de polychimiothérapie antinéoplasique/usage thérapeutique , Protocoles de polychimiothérapie antinéoplasique/effets indésirables , Tumeurs du sein/traitement médicamenteux , Tumeurs du sein/mortalité , Tumeurs du sein/anatomopathologie , Tumeurs du sein/métabolisme , Traitement médicamenteux adjuvant/méthodes , Rythme circadien , Survie sans rechute , Stadification tumorale , Tamoxifène/administration et posologie , Tamoxifène/usage thérapeutique , Résultat thérapeutique , Études prospectivesRÉSUMÉ
New therapies are being developed for breast cancer, and in this process, some "old" biomarkers are reutilized and given a new purpose. It is not always recognized that by changing a biomarker's intended use, a new biomarker assay is created. The Ki-67 biomarker is typically assessed by immunohistochemistry (IHC) to provide a proliferative index in breast cancer. Canadian laboratories assessed the analytical performance and diagnostic accuracy of their Ki-67 IHC laboratory-developed tests (LDTs) of relevance for the LDTs' clinical utility. Canadian clinical IHC laboratories enrolled in the Canadian Biomarker Quality Assurance Pilot Run for Ki-67 in breast cancer by invitation. The Dako Ki-67 IHC pharmDx assay was employed as a study reference assay. The Dako central laboratory was the reference laboratory. Participants received unstained slides of breast cancer tissue microarrays with 32 cases and performed their in-house Ki-67 assays. The results were assessed using QuPath, an open-source software application for bioimage analysis. Positive percent agreement (PPA, sensitivity) and negative percent agreement (NPA, specificity) were calculated against the Dako Ki-67 IHC pharmDx assay for 5%, 10%, 20%, and 30% cutoffs. Overall, PPA and NPA varied depending on the selected cutoff; participants were more successful with 5% and 10%, than with 20% and 30% cutoffs. Only 4 of 16 laboratories had robust IHC protocols with acceptable PPA for all cutoffs. The lowest PPA for the 5% cutoff was 85%, for 10% was 63%, for 20% was 14%, and for 30% was 13%. The lowest NPA for the 5% cutoff was 50%, for 10% was 33%, for 20% was 50%, and for 30% was 57%. Despite many years of international efforts to standardize IHC testing for Ki-67 in breast cancer, our results indicate that Canadian clinical LDTs have a wide analytical sensitivity range and poor agreement for 20% and 30% cutoffs. The poor agreement was not due to the readout but rather due to IHC protocol conditions. International Ki-67 in Breast Cancer Working Group (IKWG) recommendations related to Ki-67 IHC standardization cannot take full effect without reliable fit-for-purpose reference materials that are required for the initial assay calibration, assay performance monitoring, and proficiency testing.
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Tumeurs du sein , Immunohistochimie , Antigène KI-67 , Humains , Antigène KI-67/métabolisme , Antigène KI-67/analyse , Tumeurs du sein/métabolisme , Tumeurs du sein/diagnostic , Tumeurs du sein/anatomopathologie , Femelle , Immunohistochimie/méthodes , Marqueurs biologiques tumoraux/métabolisme , Marqueurs biologiques tumoraux/analyse , Canada , Sensibilité et spécificité , Analyse sur puce à tissus/méthodesRÉSUMÉ
Artificial intelligence (AI)-assisted diagnosis is an ongoing revolution in pathology. However, a frequent drawback of AI models is their propension to make decisions based rather on bias in training dataset than on concrete biological features, thus weakening pathologists' trust in these tools. Technically, it is well known that microscopic images are altered by tissue processing and staining procedures, being one of the main sources of bias in machine learning for digital pathology. So as to deal with it, many teams have written about color normalization and augmentation methods. However, only a few of them have monitored their effects on bias reduction and model generalizability. In our study, two methods for stain augmentation (AugmentHE) and fast normalization (HEnorm) have been created and their effect on bias reduction has been monitored. Actually, they have also been compared to previously described strategies. To that end, a multicenter dataset created for breast cancer histological grading has been used. Thanks to it, classification models have been trained in a single center before assessing its performance in other centers images. This setting led to extensively monitor bias reduction while providing accurate insight of both augmentation and normalization methods. AugmentHE provided an 81% increase in color dispersion compared to geometric augmentations only. In addition, every classification model that involved AugmentHE presented a significant increase in the area under receiving operator characteristic curve (AUC) over the widely used RGB shift. More precisely, AugmentHE-based models showed at least 0.14 AUC increase over RGB shift-based models. Regarding normalization, HEnorm appeared to be up to 78x faster than conventional methods. It also provided satisfying results in terms of bias reduction. Altogether, our pipeline composed of AugmentHE and HEnorm improved AUC on biased data by up to 21.7% compared to usual augmentations. Conventional normalization methods coupled with AugmentHE yielded similar results while being much slower. In conclusion, we have validated an open-source tool that can be used in any deep learning-based digital pathology project on H&E whole slide images (WSI) that efficiently reduces stain-induced bias and later on might help increase pathologists' confidence when using AI-based products.
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Intelligence artificielle , Tumeurs du sein , Femelle , Humains , Agents colorants , Apprentissage machine , Coloration et marquage , Études multicentriques comme sujetRÉSUMÉ
The mechanisms of action of and resistance to trastuzumab deruxtecan (T-DXd), an anti-HER2-drug conjugate for breast cancer treatment, remain unclear. The phase 2 DAISY trial evaluated the efficacy of T-DXd in patients with HER2-overexpressing (n = 72, cohort 1), HER2-low (n = 74, cohort 2) and HER2 non-expressing (n = 40, cohort 3) metastatic breast cancer. In the full analysis set population (n = 177), the confirmed objective response rate (primary endpoint) was 70.6% (95% confidence interval (CI) 58.3-81) in cohort 1, 37.5% (95% CI 26.4-49.7) in cohort 2 and 29.7% (95% CI 15.9-47) in cohort 3. The primary endpoint was met in cohorts 1 and 2. Secondary endpoints included safety. No new safety signals were observed. During treatment, HER2-expressing tumors (n = 4) presented strong T-DXd staining. Conversely, HER2 immunohistochemistry 0 samples (n = 3) presented no or very few T-DXd staining (Pearson correlation coefficient r = 0.75, P = 0.053). Among patients with HER2 immunohistochemistry 0 metastatic breast cancer, 5 of 14 (35.7%, 95% CI 12.8-64.9) with ERBB2 expression below the median presented a confirmed objective response as compared to 3 of 10 (30%, 95% CI 6.7-65.2) with ERBB2 expression above the median. Although HER2 expression is a determinant of T-DXd efficacy, our study suggests that additional mechanisms may also be involved. (ClinicalTrials.gov identifier NCT04132960 .).
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Tumeurs du sein , Immunoconjugués , Humains , Femelle , Tumeurs du sein/traitement médicamenteux , Tumeurs du sein/génétique , Tumeurs du sein/anatomopathologie , Trastuzumab/usage thérapeutique , Récepteur ErbB-2/génétique , Récepteur ErbB-2/métabolisme , Camptothécine/usage thérapeutiqueRÉSUMÉ
Breast cancer is the most common malignancy in woman, and its associated mortality is still rising worldwide. Among all the different subtypes of breast cancer, invasive lobular carcinoma (ILC) is the second most frequent. Several histological variants of ILC currently exist such as solid, alveolar, pleomorphic, tubulo-lobular, and mixed types. Recently, a new variant of ILC with a papillary growth pattern has been described. Here, we make a review of the literature and report the sixth case of a woman suffering from this very uncommon variant. Of note, she had a concomitant axillary lymph node metastasis, a manifestation not yet described so far. Molecular analysis showed CDH1 and PIK3CA mutations, along with similar quantitative chromosomal alterations in both primary and metastasis. Because ILC and papillary carcinoma are managed differently, our aim here is to raise awareness among the pathologists to avoid misdiagnosis of this unusual variant and subsequent inappropriate treatment.
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Tumeurs du sein , Carcinome canalaire du sein , Carcinome lobulaire , Femelle , Humains , Carcinome lobulaire/diagnostic , Carcinome lobulaire/génétique , Carcinome lobulaire/anatomopathologie , Tumeurs du sein/anatomopathologie , Métastase lymphatique , Carcinome canalaire du sein/anatomopathologieRÉSUMÉ
PURPOSE: We aimed to determine the pattern of isolated local recurrences (ILR) in women with stage II-III hormone receptor-positive and human epidermal growth factor receptor 2 breast cancer (HR + /HER2-BC) after 10-year follow-up. METHODS: UNICANCER-PACS 01 and PACS 04 trials included 5,008 women with T1-T3 and N1-N3 to evaluate the efficacy of different anthracycline ± taxanes-containing regimens after modified mastectomy or lumpectomy plus axillary lymph node dissection. We analyzed the data from 2,932 women with HR + /HER2- BC to evaluate the cumulative incidence of ILR and describe the factors associated with ILR. RESULTS: After a median follow-up of 9.1 years (95% CI 9.0-9.2 years), the cumulative incidence of ILR increased steadily between 1 and 10 years from 0.2% to 2.5%. The multivariable analysis showed that older age (subhazard ratios [sHR] = 0.95, 95% CI 0.92-0.99) and mastectomy (sHR = 0.39, 95% CI 0.17-0.86) were associated with lower risk of ILR, and no adjuvant endocrine therapy (sHR = 2.73, 95% CI 1.32 7-5.67) with increased risk of ILR. CONCLUSION: In this population of high-risk patients with localized HR + /HER2- BC, the risk of ILR was low but remained constant over 10 years. Younger age at diagnosis, breast-conserving surgery, and adjuvant endocrine therapy were independent risk factors of ILR.
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Tumeurs du sein , Femelle , Humains , Tumeurs du sein/traitement médicamenteux , Tumeurs du sein/chirurgie , Tumeurs du sein/métabolisme , Mastectomie , Études de suivi , Récidive tumorale locale/épidémiologie , Récidive tumorale locale/chirurgie , Noeuds lymphatiques/anatomopathologie , Facteurs de risqueRÉSUMÉ
PURPOSE: We compared the mutational profile of second breast cancers (SBC) following first ipislateral hormone receptor-positive breast cancers of patient-matched tumors to distinguish new primaries from true recurrences. EXPERIMENTAL DESIGN: Targeted next-generation sequencing using the Oncomine Tumor Mutation Load Assay. Variants were filtered according to their allele frequency ≥ 5%, read count ≥ 5X, and genomic effect and annotation. Whole genome comparative genomic hybridization array (CGH) was also performed to evaluate clonality. RESULTS: Among the 131 eligible patients, 96 paired first breast cancer (FBC) and SBC were successfully sequenced and analyzed. Unshared variants specific to the FBC and SBC were identified in 71.9% and 61.5%, respectively. Paired samples exhibited similar frequency of gene variants, median number of variants per sample, and variant allele frequency of the reported variants except for GATA3. Among the 30 most frequent gene alterations, ARIDIA, NSD2, and SETD2 had statistically significant discordance rates in paired samples. Seventeen paired samples (17.7%) exhibited common variants and were considered true recurrences; these patients had a trend for less favorable survival outcomes. Among the 8 patients with available tissue for CGH analysis and considered new primaries by comparison of the mutation profiles, 4 patients had clonally related tumors. CONCLUSIONS: Patient-matched FBC and SBC analysis revealed that only a minority of patients exhibited common gene variants between the first and second tumor. Further analysis using larger cohorts, preferably using single-cell analyses to account for clonality, might better select patients with true recurrences and thereby better inform the decision-making process.
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Tumeurs du sein , Humains , Femelle , Tumeurs du sein/génétique , Tumeurs du sein/anatomopathologie , Hybridation génomique comparative , Mutation , Génomique , RécidiveRÉSUMÉ
Triple-negative breast cancer (TNBC) is a rare cancer, characterized by high metastatic potential and poor prognosis, and has limited treatment options. The current standard of care in nonmetastatic settings is neoadjuvant chemotherapy (NACT), but treatment efficacy varies substantially across patients. This heterogeneity is still poorly understood, partly due to the paucity of curated TNBC data. Here we investigate the use of machine learning (ML) leveraging whole-slide images and clinical information to predict, at diagnosis, the histological response to NACT for early TNBC women patients. To overcome the biases of small-scale studies while respecting data privacy, we conducted a multicentric TNBC study using federated learning, in which patient data remain secured behind hospitals' firewalls. We show that local ML models relying on whole-slide images can predict response to NACT but that collaborative training of ML models further improves performance, on par with the best current approaches in which ML models are trained using time-consuming expert annotations. Our ML model is interpretable and is sensitive to specific histological patterns. This proof of concept study, in which federated learning is applied to real-world datasets, paves the way for future biomarker discovery using unprecedentedly large datasets.
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Traitement néoadjuvant , Tumeurs du sein triple-négatives , Humains , Femelle , Traitement néoadjuvant/méthodes , Tumeurs du sein triple-négatives/traitement médicamenteux , Tumeurs du sein triple-négatives/anatomopathologie , Protocoles de polychimiothérapie antinéoplasique/usage thérapeutique , Résultat thérapeutiqueSujet(s)
Adénomyoépithéliome , Tumeurs du sein , Tumeurs colorectales héréditaires sans polypose , Humains , Femelle , Adénomyoépithéliome/diagnostic , Adénomyoépithéliome/chirurgie , Adénomyoépithéliome/anatomopathologie , Tumeurs colorectales héréditaires sans polypose/complications , Tumeurs colorectales héréditaires sans polypose/diagnostic , Région mammaire/chirurgie , Région mammaire/anatomopathologieRÉSUMÉ
Atezolizumab in combination with nab-paclitaxel has been introduced for the treatment of locally advanced or recurrent triple negative breast cancer (TNBC). Patient selection relies on the use of immunohistochemistry using a specific monoclonal PD-L1 antibody (clone SP142) in a tightly controlled companion diagnostic test (CDx) with a defined interpretative algorithm. Currently there are no standardized recommendations for selecting the optimal tissue to be tested and there is limited data to support decision making, raising the possibility that tissue selection may bias test results. We compared PD-L1 SP142 assessment in a collection of 73 TNBC cases with matched core biopsies and excision samples. There was good correlation between PD-L1-positive core biopsy and subsequent excision, but we found considerable discrepancy between PD-L1 negative core biopsy and matched excision, with a third of cases found negative on core biopsies converting to positive upon examination of the excision tissue. In view of these findings, we developed a workflow for the clinical testing of TNBC for PD-L1 and implemented it in a central referral laboratory. We present audit data from the clinical PD-L1 testing relating to 2 years of activities, indicating that implementation of this workflow results in positivity rates in our population of TNBC similar to those of IMpassion130 clinical trial. We also developed an online atlas with a precise numerical annotation to aid pathologists in the interpretation of PD-L1 scoring in TNBC.
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Tumeurs du sein triple-négatives , Anticorps monoclonaux/usage thérapeutique , Antigène CD274 , Humains , Immunohistochimie , Récidive tumorale locale , Tumeurs du sein triple-négatives/diagnostic , Tumeurs du sein triple-négatives/anatomopathologieRÉSUMÉ
The importance of integrating biomarkers into the TNM staging has been emphasized in the 8th Edition of the American Joint Committee on Cancer (AJCC) Staging system. In a pooled analysis of 2148 TNBC-patients in the adjuvant setting, TILs are found to strongly up and downstage traditional pathological-staging in the Pathological and Clinical Prognostic Stage Groups from the AJJC 8th edition Cancer Staging System. This suggest that clinical and research studies on TNBC should take TILs into account in addition to stage, as for example patients with stage II TNBC and high TILs have a better outcome than patients with stage I and low TILs.
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HER2 is an important prognostic and predictive biomarker in breast cancer. Its detection makes it possible to define which patients will benefit from a targeted treatment. While assessment of HER2 status by immunohistochemistry in positive vs negative categories is well implemented and reproducible, the introduction of a new "HER2-low" category could raise some concerns about its scoring and reproducibility. We herein described the current HER2 testing methods and the application of innovative machine learning techniques to improve these determinations, as well as the main challenges and opportunities related to the implementation of digital pathology in the up-and-coming AI era.
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Intelligence artificielle , Tumeurs du sein/composition chimique , Tumeurs du sein/diagnostic , Récepteur ErbB-2/analyse , Algorithmes , Tumeurs du sein/génétique , Diagnostic assisté par ordinateur , Femelle , Amplification de gène , Gènes erbB-2 , Humains , Apprentissage machine , Guides de bonnes pratiques cliniques comme sujet , Reproductibilité des résultatsRÉSUMÉ
The last international guidelines on HER2 determination in breast cancer have been updated in 2018 by the American Society of Clinical Oncology and College of American Pathologists, on the basis of a twenty-year practice and results of numerous clinical trials. Moreover, the emerging HER2-low concept for 1+ and 2+ non amplified breast cancers lead to refine French practices for HER2 status assessment. The GEFPICS group, composed of expert pathologists, herein presents the latest French recommendations for HER2 status evaluation in breast cancer, taking into account the ASCO/CAP guidelines and introducing the HER2-low concept. In the era of personalized medicine, HER2 status assessment remains one of the most important biomarkers in breast cancer and its quality guaranties the optimal patients' care. French pathologists' commitment in theranostic biomarker quality is more than ever required to provide the most efficient cares in oncology.
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Tumeurs du sein , Marqueurs biologiques tumoraux , Tumeurs du sein/diagnostic , Tumeurs du sein/génétique , Femelle , Humains , Immunohistochimie , Hybridation fluorescente in situ , Récepteur ErbB-2/génétiqueRÉSUMÉ
High stromal tumor-infiltrating lymphocytes (sTILs) in triple-negative breast cancer (TNBC) are associated with pathological complete response (pCR) after neoadjuvant chemotherapy (NAC). Histopathological assessment of sTILs in TNBC biopsies is characterized by substantial interobserver variability, but it is unknown whether this affects its association with pCR. Here, we aimed to investigate the degree of interobserver variability in an international study, and its impact on the relationship between sTILs and pCR. Forty pathologists assessed sTILs as a percentage in digitalized biopsy slides, originating from 41 TNBC patients who were treated with NAC followed by surgery. Pathological response was quantified by the MD Anderson Residual Cancer Burden (RCB) score. Intraclass correlation coefficients (ICCs) were calculated per pathologist duo and Bland-Altman plots were constructed. The relation between sTILs and pCR or RCB class was investigated. The ICCs ranged from -0.376 to 0.947 (mean: 0.659), indicating substantial interobserver variability. Nevertheless, high sTILs scores were significantly associated with pCR for 36 participants (90%), and with RCB class for eight participants (20%). Post hoc sTILs cutoffs at 20% and 40% resulted in variable associations with pCR. The sTILs in TNBC with RCB-II and RCB-III were intermediate to those of RCB-0 and RCB-I, with lowest sTILs observed in RCB-I. However, the limited number of RCB-I cases precludes any definite conclusions due to lack of power, and this observation therefore requires further investigation. In conclusion, sTILs are a robust marker for pCR at the group level. However, if sTILs are to be used to guide the NAC scheme for individual patients, the observed interobserver variability might substantially affect the chance of obtaining a pCR. Future studies should determine the 'ideal' sTILs threshold, and attempt to fine-tune the patient selection for sTILs-based de-escalation of NAC regimens. At present, there is insufficient evidence for robust and reproducible sTILs-guided therapeutic decisions.