Advancing Artificial Intelligence Integration Into the Pathology Workflow: Exploring Opportunities in Gastrointestinal Tract Biopsies.

This review aims to present a comprehensive overview of the current landscape of artificial intelligence (AI) applications in the analysis of tubular gastrointestinal biopsies. These publications cover a spectrum of conditions, ranging from inflammatory ailments to malignancies. Moving beyond the conventional diagnosis based on hematoxylin and eosin-stained whole-slide images, the review explores additional implications of AI, including its involvement in interpreting immunohistochemical results, molecular subtyping, and the identification of cellular spatial biomarkers. Furthermore, the review examines how AI can contribute to enhancing the quality and control of diagnostic processes, introducing new workflow options, and addressing the limitations and caveats associated with current AI platforms in this context.

Utility of pathologist panels for achieving consensus in NASH histologic scoring in clinical trials: Data from a phase 3 study.

BACKGROUND: Liver histopathologic assessment is the accepted surrogate endpoint in NASH trials; however, the scoring of NASH Clinical Research Network (CRN) histologic parameters is limited by intraobserver and interobserver variability. We designed a consensus panel approach to minimize variability when using this scoring system. We assessed agreement between readers, estimated linear weighted kappas between 2 panels, compared them with published pairwise kappa estimates, and addressed how agreement or disagreement might impact the precision and validity of the surrogate efficacy endpoint in NASH trials. METHODS: Two panels, each comprising 3 liver fellowship-trained pathologists who underwent NASH histology training, independently evaluated scanned whole slide images, scoring fibrosis, inflammation, hepatocyte ballooning, and steatosis from baseline and month 18 biopsies for 100 patients from the precirrhotic NASH study REGENERATE. The consensus score for each parameter was defined as agreement by ≥2 pathologists. If consensus was not reached, all 3 pathologists read the slide jointly to achieve a consensus score. RESULTS: Between the 2 panels, the consensus was 97%-99% for steatosis, 91%-93% for fibrosis, 88%-92% for hepatocyte ballooning, and 84%-91% for inflammation. Linear weighted kappa scores between panels were similar to published NASH CRN values. CONCLUSIONS: A panel of 3 trained pathologists independently scoring 4 NASH CRN histology parameters produced high consensus rates. Interpanel kappa values were comparable to NASH CRN metrics, supporting the accuracy and reproducibility of this method. The high concordance for fibrosis scoring was reassuring, as fibrosis is predictive of liver-specific outcomes and all-cause mortality.

Artificial Intelligence Enables Quantitative Assessment of Ulcerative Colitis Histology.

Ulcerative colitis is a chronic inflammatory bowel disease that is characterized by a relapsing and remitting course. Assessment of disease activity critically informs treatment decisions. In addition to endoscopic remission, histologic remission is emerging as a treatment target and a key factor in the evaluation of disease activity and therapeutic efficacy. However, manual pathologist evaluation is semiquantitative and limited in granularity. Machine learning approaches are increasingly being developed to aid pathologists in accurate and reproducible scoring of histology, enabling precise quantitation of clinically relevant features. Here, we report the development and validation of convolutional neural network models that quantify histologic features pertinent to ulcerative colitis disease activity, directly from hematoxylin and eosin-stained whole slide images. Tissue and cell model predictions were used to generate quantitative human-interpretable features to fully characterize the histology samples. Tissue and cell predictions showed comparable agreement to pathologist annotations, and the extracted slide-level human-interpretable features demonstrated strong correlations with disease severity and pathologist-assigned Nancy histological index scores. Moreover, using a random forest classifier based on 13 human-interpretable features derived from the tissue and cell models, we were able to accurately predict Nancy histological index scores, with a weighted kappa (κ = 0.91) and Spearman correlation (⍴ = 0.89, P < .001) when compared with pathologist consensus Nancy histological index scores. We were also able to predict histologic remission, based on the absence of neutrophil extravasation, with a high accuracy of 0.97. This work demonstrates the potential of computer vision to enable a standardized and robust assessment of ulcerative colitis histopathology for translational research and improved evaluation of disease activity and prognosis.

Somatic mutations in collagens are associated with a distinct tumor environment and overall survival in gastric cancer.

BACKGROUND: Gastric cancer is a heterogeneous disease with poorly understood genetic and microenvironmental factors. Mutations in collagen genes are associated with genetic diseases that compromise tissue integrity, but their role in tumor progression has not been extensively reported. Aberrant collagen expression has been long associated with malignant tumor growth, invasion, chemoresistance, and patient outcomes. We hypothesized that somatic mutations in collagens could functionally alter the tumor extracellular matrix. METHODS: We used publicly available datasets including The Tumor Cancer Genome Atlas (TCGA) to interrogate somatic mutations in collagens in stomach adenocarcinomas. To demonstrate that collagens were significantly mutated above background mutation rates, we used a moderated Kolmogorov-Smirnov test along with combination analysis with a bootstrap approach to define the background accounting for mutation rates. Association between mutations and clinicopathological features was evaluated by Fisher or chi-squared tests. Association with overall survival was assessed by Kaplan-Meier and the Cox-Proportional Hazards Model. Gene Set Enrichment Analysis was used to interrogate pathways. Immunohistochemistry and in situ hybridization tested expression of COL7A1 in stomach tumors. RESULTS: In stomach adenocarcinomas, we identified individual collagen genes and sets of collagen genes harboring somatic mutations at a high frequency compared to background in both microsatellite stable, and microsatellite instable tumors in TCGA. Many of the missense mutations resemble the same types of loss of function mutations in collagenopathies that disrupt tissue formation and destabilize cells providing guidance to interpret the somatic mutations. We identified combinations of somatic mutations in collagens associated with overall survival, with a distinctive tumor microenvironment marked by lower matrisome expression and immune cell signatures. Truncation mutations were strongly associated with improved outcomes suggesting that loss of expression of secreted collagens impact tumor progression and treatment response. Germline collagenopathy variants guided interpretation of impactful somatic mutations on tumors. CONCLUSIONS: These observations highlight that many collagens, expressed in non-physiologically relevant conditions in tumors, harbor impactful somatic mutations in tumors, suggesting new approaches for classification and therapy development in stomach cancer. In sum, these findings demonstrate how classification of tumors by collagen mutations identified strong links between specific genotypes and the tumor environment.

Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes.

Computational methods have made substantial progress in improving the accuracy and throughput of pathology workflows for diagnostic, prognostic, and genomic prediction. Still, lack of interpretability remains a significant barrier to clinical integration. We present an approach for predicting clinically-relevant molecular phenotypes from whole-slide histopathology images using human-interpretable image features (HIFs). Our method leverages >1.6 million annotations from board-certified pathologists across >5700 samples to train deep learning models for cell and tissue classification that can exhaustively map whole-slide images at two and four micron-resolution. Cell- and tissue-type model outputs are combined into 607 HIFs that quantify specific and biologically-relevant characteristics across five cancer types. We demonstrate that these HIFs correlate with well-known markers of the tumor microenvironment and can predict diverse molecular signatures (AUROC 0.601-0.864), including expression of four immune checkpoint proteins and homologous recombination deficiency, with performance comparable to 'black-box' methods. Our HIF-based approach provides a comprehensive, quantitative, and interpretable window into the composition and spatial architecture of the tumor microenvironment.

Elastin in the Tumor Microenvironment.

Elastic fibers are found in the extracellular matrix (ECM) of tissues requiring resilience and depend on elasticity. Elastin and its degradation products have multiple roles in the oncologic process. In many malignancies, the remodeled ECM expresses high levels of the elastin protein which may have either positive or negative effects on tumor growth. Elastin cross-linking with other ECM components and the enzymes governing this process all have effects on tumorigenesis. Elastases, and specifically neutrophil elastase, are key drivers of invasion and metastasis and therefore are important targets for inhibition. Elastin degradation leads to the generation of bioactive fragments and elastin-derived peptides that further modulate tumor growth and spread. Interestingly, elastin-like peptides (ELP) and elastin-derived peptides (EDP) may also be utilized as nano-carriers to combat tumor growth. EDPs drive tumor development in a variety of ways, and specifically targeting EDPs and their binding proteins are major objectives for ongoing and future anti-cancer therapies. Research on both the direct anti-cancer activity and the drug delivery capabilities of ELPs is another area likely to result in novel therapeutic agents in the near future.

Smooth muscle tumors of the gastrointestinal tract: an analysis of prognostic features in 407 cases.

Smooth muscle tumors represent the second most common mural mesenchymal neoplasm in the gastrointestinal tract, but established criteria for prognostic assessment of these tumors are lacking. A large cohort of surgically resected intramural gastrointestinal smooth muscle tumors from 31 institutions was analyzed to identify potential prognostic features. Pathologic features were assessed by expert gastrointestinal and/or soft tissue pathologists at each center. Immunohistochemical confirmation was required. A total of 407 cases from the esophagus (n = 97, 24%), stomach (n = 180, 44%), small bowel (n = 74, 18%), and colorectum (n = 56, 14%) were identified. Patients ranged in age from 19 to 92 years (mean 55 years), with a slight female predominance (57%). Mean tumor size was 5.4 cm, with the largest tumor measuring 29 cm. Disease progression following surgery, defined as local recurrence, metastasis, or disease-related death, occurred in 56 patients (14%). Colorectal tumors were most likely to progress, followed by small bowel and gastric tumors. None of the esophageal tumors in this series progressed. Receiver operator characteristic analysis identified optimal cutoffs of 9.8 cm and 3 mitoses/5 mm2 for discriminating between progressive and non-progressive tumors. Histologic features strongly associated with progression by univariate analysis included moderate-to-severe atypia, high cellularity, abnormal differentiation (defined as differentiation not closely resembling that of normal smooth muscle), tumor necrosis, mucosal ulceration, lamina propria involvement, and serosal involvement (P < 0.0001 for all features). Age, sex, and margin status were not significantly associated with progression (P = 0.23, 0.82, and 0.07, respectively). A risk assessment table was created based on tumor site, size, and mitotic count, and Kaplan-Meier plots of progression-free survival for each subgroup revealed progression-based tiers. Based on our findings, it appears that nonesophageal gastrointestinal smooth muscle tumors measuring >10 cm and/or showing ≥3 mitoses/5 mm2 may behave aggressively, and therefore close clinical follow-up is recommended in these cases.

Expression of Indoleamine 2, 3-dioxygenase 1 (IDO1) and Tryptophanyl-tRNA Synthetase (WARS) in Gastric Cancer Molecular Subtypes.

AIMS: Developments in genomic pathology have led to novel molecular classification schemes in gastric cancers. Two of these new subtypes, Epstein-Barr virus (EBV)-associated and microsatellite instability-high (MSI-H), are associated with a dominant T-cell-mediated immune response. The roles of the immune modulators, indoleamine 2, 3-dioxygenase 1 (IDO1) and tryptophanyl-tRNA synthetase (WARS), have not been investigated in the context of this classification. METHODS AND RESULTS: Using in situ hybridization and immunohistochemistry we subclassified 421 primary gastric adenocarcinomas into 5 subtypes, EBV-associated, epithelial to mesenchymal transition, MSI-H, p53-aberrant, and p53-wildtype tumors. Tumor-infiltrative lymphocytes were counted and protein expression of IDO1 and WARS was graded on tissue microarrays of these 421 tumors. High tumor-infiltrative lymphocytes as well as high expression of both IDO1 and WARS was found in EBV and MSI-H tumors. The prognostic effects of IDO1 and WARS expression were tumor subtype dependent. Although high expression levels of IDO1 and WARS were associated with poor prognosis in p53-aberrant, p53-wildtype, and all cancers combined, WARS expression was associated with better prognosis in MSI tumors. CONCLUSIONS: The immunomodulators, IDO1 and WARs, are upregulated and have prognostic significance in EBV-associated and MSI-H tumors. Novel therapies targeting these proteins should be considered in the treatment of these patients.

Stromal ColXα1 expression correlates with tumor-infiltrating lymphocytes and predicts adjuvant therapy outcome in ER-positive/HER2-positive breast cancer.

BACKGROUND: The breast cancer microenvironment contributes to tumor progression and response to chemotherapy. Previously, we reported that increased stromal Type X collagen α1 (ColXα1) and low TILs correlated with poor pathologic response to neoadjuvant therapy in estrogen receptor and HER2-positive (ER+/HER2+) breast cancer. Here, we investigate the relationship of ColXα1 and long-term outcome of ER+/HER2+ breast cancer patients in an adjuvant setting. METHODS: A total of 164 cases with at least 5-year follow-up were included. Immunohistochemistry for ColXα1 was performed on whole tumor sections. Associations between ColXα1expression, clinical pathological features, and outcomes were analyzed. RESULTS: ColXα1 expression was directly proportional to the amount of tumor associated stroma (p = 0.024) and inversely proportional to TILs. Increased ColXα1 was significantly associated with shorter disease free survival and overall survival by univariate analysis. In multivariate analysis, OS was lower in ColXα1 expressing (HR = 2.1; 95% CI = 1.2-3.9) tumors of older patients (> = 58 years) (HR = 5.3; 95% CI = 1.7-17) with higher stage (HR = 2.6; 95% CI = 1.3-5.2). Similarly, DFS was lower in ColXα1 expressing (HR = 1.8; 95% CI = 1.6-5.7) tumors of older patients (HR = 3.2; 95% CI = 1.3-7.8) with higher stage (HR = 2.7; 95% CI = 1.6-5.7) and low TILs. In low PR+ tumors, higher ColXα1 expression was associated with poorer prognosis. CONCLUSION: ColXα1 expression is associated with poor disease free survival and overall survival in ER+/HER2+ breast cancer. This study provides further support for the prognostic utility of ColXα1 as a breast cancer associated stromal factor that predicts response to chemotherapy.

Cytokeratin 7-negative and GATA binding protein 3-negative breast cancers: Clinicopathological features and prognostic significance.

BACKGROUND: Cytokeratin 7 (CK7) and GATA binding protein 3 (GATA3) are considered as immunohistochemical hallmarks of breast cancers; however, there are breast tumors lacking these markers. Clinicopathological characterization of CK7 negative breast cancer has not been addressed previously and similar studies on GATA3 negative tumors are limited. METHODS: This study included 196 consecutive cases of Nottingham Grade 3 breast cancers with 159 cases of Grade 1 and Grade 2 tumors for comparison. CK7 and GATA3 expression was correlated with patient's age, histological type, pathological grade and stage, hormone receptor status, molecular subtype and overall survival. RESULTS: CK7 negativity was seen in 13% of Grade 3, 9% of Grade 2, and 2% of Grade 1 cases (P = 0.0457). Similarly, 28% of Grade 3, 5% of Grade 2 and 2% of Grade 1 cases were GATA3 negative (P < 0.0001). CK7 negative tumors did not show association with other clinicopathological parameters. GATA3 negative tumors were enriched in the basal-like molecular subgroup and were associated with negative estrogen receptor (ER) and negative progesterone receptor (PR) statuses. Both CK7 and GATA3 expression showed no association with overall survival in patients with Grade 3 tumor. CONCLUSIONS: This is the first study to characterize CK7 negative breast tumors in the context of clinicopathology. Profiling the CK7 negative and GATA3 negative breast cancers helps to understand the biology of these specific tumor subgroups and may aid in their diagnosis.

TKI-resistant ALK-rearranged lung adenocarcinoma with secondary CTNNB1 p.S45V and tertiary ALK p.I1171N mutations.

Anaplastic lymphoma kinase (ALK)-rearranged non-small cell lung cancer (NSCLC) is an important molecular subgroup of tumors that are typically sensitive to tyrosine kinase inhibitors (TKIs). Although a substantial portion of patients benefit from TKIs, this approach is complicated by intrinsic and acquired resistance. We report a patient with ALK-rearranged NSCLC who showed an initial response to targeted therapy, but developed resistance to multiple TKIs. Serial comprehensive genomic profiling (CGP) was performed at four independent points during the clinical course. We review the pathology and clonal progression of the tumor, with CGP identifying a secondary CTNNB1 p.S45V mutation after the initiation of targeted therapy, followed by tertiary ALK p.I1171N. The presence of an alteration in a second oncogenic driver gene suggests a possible mechanism for resistance, and a secondary therapeutic target. Due to the involvement of Wnt signaling in the pathogenesis of many tumors and its association with immune evasion, a variety of therapeutic strategies are being developed to target this pathway. This case exemplifies the challenges of targeted therapeutics in the face of tumor progression, as well as the increasing role of genomics in understanding tumor biology.

Retrospective Analysis Confirms Tetracycline Quadruple as Best Helicobacter pylori Regimen in the USA.

BACKGROUND: Declining Helicobacter pylori (H. pylori) eradication rates have prompted a switch in first-line therapy from standard triple (PPI, clarithromycin, and amoxicillin) to bismuth-based quadruple therapy. A caveat of the ACG 2017 H. pylori treatment guidelines was a paucity of recent US eradication data. AIM: To determine Rhode Island H. pylori eradication data, in the largest US study from the last two decades. METHODS: Electronic records were queried for patients with H. pylori infection diagnosed by pathology, urea breath test, or stool antigen from 2015 to 2017. Demographics, diagnostic test, treatment regimen, and test of cure were extracted. Eradication rates were calculated, and treatment regimens were compared. RESULTS: A total of 1710 patients were identified (64% female): 825 (46%) diagnosed by breath test, 755 (42%) by biopsy, and 191 (12%) by stool antigen. Full data were obtained on 1101 patients. Seven regimens were used: quadruple (64%), triple (25%), doxycycline quadruple (5%), and miscellaneous (6%). Quadruple was superior to triple: (85% vs. 75%, P = 0.002), quadruple 14 days versus triple 14 days (87% vs. 79%, P = 0.0052), quadruple 10 days versus triple 10 days (77% vs. 67%, P = 0.33). Increased therapy length improved eradication (quadruple 14 days  vs. 10 days, 87% vs. 77%, P = 0.002; triple 14 days  versus 10 days 79% vs. 67%, P = 0.13). Finally, substituting doxycycline for tetracycline yielded lower eradication (85% vs. 67%, P = 0.006). CONCLUSION: Quadruple therapy is superior to triple therapy within the Rhode Island population. Fourteen-day therapy achieves superior eradication compared to 10-day therapy, and doxycycline is inferior to tetracycline for quadruple therapy. Our findings support adherence to ACG and international guidelines advising 14-day quadruple therapy.

Immune environment in serrated lesions of the colon: intraepithelial lymphocyte density, PD-1, and PD-L1 expression correlate with serrated neoplasia pathway progression.

The serrated neoplasia pathway accounts for approximately 20% of colorectal carcinomas (CRCs). Sessile serrated adenomas (SSAs), the main precursor lesion of the serrated pathway, are molecularly driven by MLH1 promoter methylation and microsatellite instability (MSI) in their progression to CRC. MSI-high (MSI-H) lesions are highly immunogenic and associated with a high density of tumor-infiltrating lymphocytes. Our study's aim was to determine how the kinetics of this immune environment relates to SSAs in their progression through low-grade (SSA-LD) to high-grade dysplasia (SSA-HD) and CRC. We analyzed 74 cases (16 CRCs, 14 SSAs-HD, and 44 SSAs-LD). Cases of hyperplastic polyp and SSA without dysplasia were analyzed for comparison. MSI status, intraepithelial lymphocyte (IEL) density, and immune checkpoint expression were assessed by immunohistochemistry for mismatch repair proteins, CD3, and PD-1/PD-L1, respectively. Average IEL density was 12, 18.6, 21.6, and 31 for SSA, SSA-LD, SSA-HD, and CRC, respectively, as opposed to 8.1 in normal colon (P < .0001). Average PD-1/PD-L1 lymphocytic expression was 1.1/1.0, 1.2/2.9, 4.8/6.9, and 12.4/15.2 in SSA, SSA-LD, SSA-HD, and CRC, respectively, compared with 0.5/0 in normal crypts (P < .0001). IEL and PD-1/PD-L1 lymphocytic expression values of MSI-H lesions were 22.6, 27.7, and 36.8, and 3/6.5, 6.2/10.6, and 18.3/17.6 in MSI-H SSA-LD, SSA-HD, and CRCs, respectively (P ranged from .0478 to .3529). PD-L1 epithelial expression was positive in 40% of SSAs, 59.1% of SSAs-LD, 100% of SSAs-HD, and 60% of CRCs (P < .0001). Increased IELs and PD-1/PD-L1 expression correlate with sequential progression of SSAs, through development of cytologic dysplasia, to CRC and MSI-H status.

ColXα1 is a stromal component that colocalizes with elastin in the breast tumor extracellular matrix.

The tumor microenvironment regulates tissue development and homeostasis, and its dysregulation contributes to neoplastic progression. Increased expression of type X collagen α-1 (ColXα1) in tumor-associated stroma correlates with poor pathologic response to neoadjuvant chemotherapy in estrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2)-positive breast cancers. Evaluation of ColXα1 expression patterns suggests a potential connection with elastin fibers. To investigate the possible interaction between ColXα1 and elastin, we evaluated the expression of ColXα1 in relation to elastin fibers in normal breast tissue, ductal carcinoma in situ, and invasive breast carcinomas at cellular and subcellular levels. Our findings demonstrate that ColXα1 colocalizes with elastin in invasive breast cancer-associated stroma by immunohistochemistry, immunofluorescence, and electron microscopy. In 212 invasive breast carcinomas, this complex was aberrantly and selectively expressed in tumor extracellular matrix in 79% of ER+/HER2-, 80% of ER+/HER2+, 76% of ER-/HER2+, and 58% of triple negative breast cancers. In contrast, ColXα1 was generally absent, while elastin was present perivascularly in normal breast tissue. ColXα1 and elastin were coexpressed in 58% of ductal carcinoma in situ (DCIS) in periductal areas. In mass-forming DCIS with desmoplastic stroma, the complex was intensely expressed in periductal areas as well as within the tumor-associated stroma in all cases. Our data suggest that the breast carcinoma neoplastic process may involve aberrant expression of ColXα1 and elastin in the tumor microenvironment emerging early at the DCIS stage. Enrichment of these complexes in tumor-associated stroma may represent a stromal signature indicative of intrinsic differences between breast cancers. These findings shed light on investigation into the role of aberrant collagen complex expression in tumorigenesis and tumor progression which may be leveraged in therapeutic and theranostic applications.

Differentiating breast carcinoma with signet ring features from gastrointestinal signet ring carcinoma: assessment of immunohistochemical markers.

Signet ring morphology is recognized throughout the gastrointestinal tract. However, this pattern may be observed in other primary sites giving rise to diagnostic challenges in the work-up of metastases. Relatively newer immunohistochemical markers have not been evaluated in this context. We assessed expression patterns of several common immunohistochemical markers in tumors with Signet ring morphology to delineate a pragmatic approach to this differential diagnosis. Primary breast and gastrointestinal carcinomas showing Signet ring features were reviewed. Non-mammary and non-gastrointestinal tumors with this morphology were included for comparison. Estrogen receptor (ER), progesterone receptor (PR), E-cadherin, CK7, CK20, GCDFP-15, mammaglobin, CDX2, GATA-3, and HepPar-1 immunohistochemistry was performed. Expression patterns were compared between breast and gastrointestinal tumors as well as lobular breast and gastric tumors. Ninety-three cases were identified: 33 breast carcinomas including 13 lobular, 50 gastrointestinal tumors including 23 gastric, and 10 from other sites. ER (sensitivity=81.8%, specificity=100%, positive predictive value (PPV)=100%, negative predictive value (NPV)=89.3%) and GATA-3 (sensitivity=100%, specificity=98%, PPV=96.8%, NPV=100%) expression were associated with breast origin. CK20 (sensitivity=66.7%, specificity=93.3%, PPV=94.1%, NPV=63.6%) and CDX2 (sensitivity=72%, specificity=100%, PPV=100%, NPV=68.9%) demonstrated the strongest discriminatory value for gastrointestinal origin. These markers exhibited similar discriminatory characteristics when comparing lobular and gastric signet ring carcinomas. In a limited trial on metastatic breast and gastric cases, these markers successfully discriminated between breast and gastric primary sites in 15 of 16 cases. ER and GATA-3 are most supportive of mammary origin and constitute an effective panel for distinguishing primary breast from primary gastrointestinal Signet ring tumors when combined with CK20 and CDX2 immunohistochemistry.

Stromal Clusterin Expression Predicts Therapeutic Response to Neoadjuvant Chemotherapy in Triple Negative Breast Cancer.

BACKGROUND: Expression of clusterin correlates with tumor progression and therapeutic response in several human malignancies, including breast cancer. However, its predictive value in the neoadjuvant setting in breast cancer remains unexplored. The objective of this explorative study was to determine whether clusterin expression in breast cancer correlated with clinical pathologic characteristics and whether its expression was predictive of response to neoadjuvant chemotherapy (NAC). MATERIALS AND METHODS: We determined the clusterin expression pattern in 72 triple negative breast cancers (TNBC) treated with NAC before surgery. Clusterin expression was evaluated by immunohistochemistry and was correlated with pathologic characteristics and response to NAC using residual cancer burden score. RESULTS: Immunohistochemistry analysis revealed a differential pattern of expression between tumor and stroma. Clusterin expression in the tumor associated stroma as opposed to expression by the neoplastic epithelium was significantly associated with neoadjuvant-treated TNBC. Low stromal clusterin, low stromal content, and high tumor-infiltrating lymphocytes were associated with a significantly greater likelihood of achieving a good pathologic response as reflected by lower residual cancer burden scores (P = .002, P = .003, and P = .001, respectively). Tumor and/or stromal clusterin expression were not associated with patient age, tumor histologic grade, stage, and lymph node status. CONCULSION: This study suggests a potential role for the assessment of stromal clusterin as a predictive biomarker for response of TNBC to neoadjuvant therapy. Further validation of this biomarker in a large study is needed.

Role of immune microenvironment in gastrointestinal stromal tumours.

AIMS: The immune microenvironment is a prognostic factor for various malignancies. The significance of key players of this immune microenvironment, including tumour-infiltrating lymphocytes (TILs) and expression of programmed death-ligand 1 (PD-L1), indoleamine 2,3-dioxygenase (IDO) and tryptophanyl-tRNA synthetase (WARS) in gastrointestinal stromal tumours (GISTs) is largely unknown. METHODS AND RESULTS: Tissue microarrays were constructed from pathology files, 1996-2016. Immunohistochemistry for PD-L1, IDO and WARS was correlated with tumour size, mitoses and outcomes. TILs expressing CD3, CD4, CD8, FoxP3 and GBP5 were counted. A total of 129 GISTs were analysed. Mean patient age was 62.5 years; 52.0% were male. Tumour location included 89 stomach (69.0%), 33 small bowel (25.6%) and seven other (5.4%). Mean tumour size was 5.6 cm; mean mitoses were 7.2 per 50 high-power field. Nineteen patients (15.0%) developed disease progression, to abdominal wall (n = 8), liver (n = 6) and elsewhere (n = 5). Median progression-free survival was 56.6 months; five patients died of disease. PD-L1 was positive in 88 of 127 tumour samples (69.0%), 114 of 127 tumours were IDO-positive (89.8%) and 60 of 127 were positive for WARS (47.2%). PD-L1 was associated with increased size (P = 0.01), necrosis (P = 0.018) and mitoses (P = 0.006). Disease progression was not associated with PD-L1 (P = 0.44), IDO (P = 0.14) or WARS (P = 0.36) expression. PD-L1-positive GISTs with CD8+ or CD3+ TILs were significantly smaller than tumours with CD8+ or CD3+ TILs. CONCLUSIONS: PD-L1 expression was associated with increased size and mitoses. High CD8+ or CD3+ TIL counts were associated with decreased PD-L1/IDO+ GIST size. PD-L1 and IDO could be significant in GIST tumour biology, which invites consideration of immunotherapy as a potential treatment option.

The Inflammatory Milieu of Eosinophilic Esophagitis: A Contemporary Review With Emphasis in Putative Immunohistochemistry and Serologic Markers.

Eosinophilic esophagitis is a chronic disease characterized by esophageal dysfunction, frequent clinical history of atopy, and eosinophilic inflammation of the esophagus. Within the esophageal mucosa, there is a wide variety of immune mediators, chemotactic factors, mediators of transcription, and markers of epithelial differentiation and integrity that are overexpressed or underexpressed in eosinophilic esophagitis, offering many candidates for biomarkers with diagnostic or prognostic potential. In this review, we summarize the results from studies performed so far to evaluate the detection of these markers by immunohistochemistry on esophageal biopsies. In addition, we briefly describe some attempts to identify markers that could be detected in serum to be used to diagnose or monitor the disease without the need of a biopsy.