Faculty Bibliography

The generative artificial intelligence (AI) model ChatGPT holds transformative prospects in medicine. The development of such models has signaled the beginning of a new era where complex biological data can be made more accessible and interpretable. ChatGPT is a natural language processing tool that can process, interpret, and summarize vast data sets. It can serve as a digital assistant for physicians and researchers, aiding in integrating medical imaging data with other multiomics data and facilitating the understanding of complex biological systems. The physician's and AI's viewpoints emphasize the value of such AI models in medicine, providing tangible examples of how this could enhance patient care. The editorial also discusses the rise of generative AI, highlighting its substantial impact in democratizing AI applications for modern medicine. While AI may not supersede health care professionals, practitioners incorporating AI into their practices could potentially have a competitive edge.

This rapid communication highlights the correlations between digital pathology-whole slide imaging (WSI) and radiomics-magnetic resonance imaging (MRI) features in triple-negative breast cancer (TNBC) patients. The research collected 12 patients who had both core needle biopsy and MRI performed to evaluate pathologic complete response (pCR). The results showed that higher collagenous values in pathology data were correlated with more homogeneity, whereas higher tumor expression values in pathology data correlated with less homogeneity in the appearance of tumors on MRI by size zone non-uniformity normalized (SZNN). Higher myxoid values in pathology data are correlated with less similarity of gray-level non-uniformity (GLN) in tumor regions on MRIs, while higher immune values in WSIs correlated with the more joint distribution of smaller-size zones by small area low gray-level emphasis (SALGE) in the tumor regions on MRIs. Pathologic complete response (pCR) was associated with collagen, tumor, and myxoid expression in WSI and GLN and SZNN in radiomic features. The correlations of WSI and radiomic features may further our understanding of the TNBC tumoral microenvironment (TME) and could be used in the future to better tailor the use of neoadjuvant chemotherapy (NAC). This communication will focus on the post-NAC MRI features correlated with pCR and their association with WSI features from core needle biopsies.

The use of social media platforms in pathology and medical laboratory science has increased in recent years, revolutionizing the way professionals in these fields interact, disseminate information, and collaborate. To gain an understanding of the current landscape regarding social media use in pathology and medical laboratory science, a novel systematic review was conducted. A search of PubMed, Medline, Embase, and Scopus was performed to identify articles evaluating social media use within pathology and medical laboratory science. Articles published in English within the previous 10 years were searched on December 22, 2022. Inclusion criteria were articles containing information regarding social media utility in pathology or laboratory medicine and related articles that mentioned specific hashtags for pathology. The review process involved analyzing the social media platforms referenced, hashtags mentioned, and the presence of international authors as key endpoints of interest. 802 publications were identified; 54 studies met inclusion criteria. Subspecialties represented were considered, but none were found to be statistically significant. X/Twitter (n = 42) was the most discussed social media platform. The top hashtags discussed were #pathJC (5.1%), #dermpathJC (4.2%), #USCAP2016 (3.4%), and #PathBoards (3.4%). Analysis of these articles provides insights into current trends, including the social media platforms referenced, hashtags used, and involvement of international authors. This review will contribute to a deeper understanding of the role and impact of social media in these fields, highlighting opportunities and challenges for future research and practice in pathology and lab medicine.

Do traditional prognostic factors fully account for the diversity of clinical behavior in breast cancer? Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer seen to have a poor prognosis, although there is great variation in clinical outcomes. Most recently, novel approaches have targeted the tumoral microenvironment (TME) to determine prognosis and tumor-associated stroma has become increasingly recognized as a potential biomarker to predict treatment response and prognosis in TNBC. The principle aim of this paper is to demonstrate an approach to stromal grading in TNBC, with consideration of its utility for predicting pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) and clinical survival outcomes. We evaluated 152 TNBC cases from the Firehose Legacy TCGA Cohort and validated our findings in a series of 110 patients from our health system. Stromal grading correlated with clinical outcomes related to prognosis and response to NAC, advanced pathologic stage, as well as clinical demographics like age over 50 years with good interobserver reliability (83.6-89.1%). Looking forward, the TME could carve out a more precision-based care in TNBC and breast cancer generally.

Triple-negative breast cancer (TNBC) is a heterogenous group of tumors. Most TNBCs are high-grade aggressive tumors, but a minority of TNBCs are not high grade, with relatively indolent behavior and specific morphologic and molecular features. We performed a clinicopathologic and molecular assessment of 18 non-high-grade TNBCs with apocrine and/or histiocytoid features. All were grade I or II with low Ki-67 (≤20%). Thirteen (72%) showed apocrine features, and 5 (28%) showed histiocytoid and lobular features. In all, 17/18 expressed the androgen receptor, and 13/13 expressed gross cystic disease fluid protein 15. Four (22.2%) patients were treated with neoadjuvant chemotherapy, but none achieved a pathologic complete response. In all, 2/18 patients (11%) had lymph node metastasis at the time of surgery. None of the cases had a recurrence or disease-specific death, with an average follow-up time of 38 months. Thirteen cases were profiled by targeted capture-based next-generation DNA sequencing. Genomic alterations (GAs) were most significant for PI3K-PKB/Akt pathway (69%) genes, including PIK3R1 (23%), PIK3CA (38%), and PTEN (23%), and RTK-RAS pathway (62%) including FGFR4 (46%) and ERBB2 (15%). TP53 GA was seen in only 31% of patients. Our findings support those on high-grade TNBCs with apocrine and/or histiocytoid features as a clinicopathologic and genetically distinct subgroup of TNBC. They can be defined by features including tubule formation, rare mitosis, low Ki-67 (≤20%), triple-negative status, expression of androgen receptor and/or gross cystic disease fluid protein 15, and GA in the PI3K-PKB/Akt and/or RTK-RAS pathway. These tumors are not sensitive to chemotherapy but have favorable clinical behavior. Tumor subtype definitions are the first step to implementing future trial designs to select these patients.

OBJECTIVES/OBJECTIVE:Stereotactic core needle biopsy (SCNB) is used in the diagnostic assessment of suspicious mammographic calcifications to rule out breast ductal carcinoma in situ (DCIS). With advances in imaging technology and increased biopsy tissue volume, the detection rate of calcifications and DCIS in SCNB is unclear. METHODS:This retrospective study included 916 consecutive SCNBs for calcifications performed on 893 patients in a 2-year period. RESULTS:We found the cancer detection rate was 27.1% (DCIS, 23.7%; invasive, 3.4%). The detection rate for calcifications was 74.8% with the standard 3 levels. Additional leveling of calcification-negative cases further increased the detection of both calcifications (to 99.4% of cases) and DCIS (to 32.9% of cases). Lobular neoplasia (LN) was diagnosed in 41 cases. Twenty-five (61.0%) cases of LN were incidental without associated calcification. Of 32 invasive carcinomas detected on SCNB, 87.5% were T1a or less, and calcifications were associated with atypical ductal hyperplasia/DCIS or LCIS. The common benign lesions associated with calcifications were fibrocystic change (32.5%), fibroadenomatous change (30.2%), and columnar cell change and hyperplasia (8.2%). CONCLUSIONS:We determined the up-to-date detection rates of calcification and DCIS in SCNB, as well as the common benign and malignant breast lesions associated with calcifications. Additional levels significantly increase the detection rate when standard levels show only stromal or scant/absent calcifications. Lobular neoplasia is often an incidental finding in SCNB for calcifications. When calcifications are present with LN, they are commonly florid, pleomorphic LCIS, or with concurrent invasive carcinoma.

Genomic alterations (GA) in NF2 tumor-suppressor gene have been associated with aggressive behavior in kidney tumors. We used comprehensive genomic profiling (CGP) to evaluate the frequencies of NF2 GA in histologic subtypes of kidney tumors and co-occurring GA in other genes and biomarkers. Advanced kidney tumors included 1875 clear cell (ccRCC), 405 papillary (pRCC), 108 chromophobe (chRCC), 171 sarcomatoid (sRCC), 61 collecting duct (cdRCC), 49 medullary (mRCC), 134 unclassified (uRCC), 906 urothelial carcinoma of renal pelvis (UC), and 147 Wilms tumors underwent hybrid-capture based CGP to evaluate all classes of GA. 192 (4.9%) of kidney tumors featured NF2 GA which were predominantly structural variant mutations (89%), followed by copy number alterations (9%). Gender and age were similar between NF2-mutant (NF2mut) and NF2-wild type (NF2wt) cohorts with male preponderance. NF2 GA frequency was highest in cdRCC (30%), sRCC (21%), uRCC (15%), and pRCC (12%) while lowest in ccRCC (3%), UC (3%) Wilms tumor (1%), and chRCC (0%). NF2 mutational status was associated with loss of Ch 22 (P < .001). NF2mut RCC harbored co-occurring GA including CDKN2A, CDKN2B, SETD2, and BAP1. VHL, PBRM1, PTEN, and FGFR3 GA were significantly more frequent in NF2wt than in NF2mut tumors. MTOR pathway GAs were uncommon in NF2mut tumors. No NF2 mutated RCC featured MSI-high or high TMB. sRCC was associated with high PD-L1 expression. PD-L1 SP142 tumoral (P = .04) and immune cells (P = .013) were more frequent in NF2mut as compared to NF2wt group. Among histologic subtypes of RCC, cdRCC, sRCC, pRCC, and uRCC are enriched in NF2 GA. Co-occurrent GA in CDKN2A/B, SETD2, and BAP1 may represent potential therapeutic targets. Higher level of PD-L1 expression in NF2mut cohort suggests that these tumors might be sensitive to immune checkpoint inhibitor therapies.

Primary breast neuroendocrine (NE) neoplasms are uncommon, and definitions harbor controversy. We retrospectively collected 73 triple-negative breast cancers (TNBC) and evaluated NE biomarker expression along with p53 aberrant staining (which correlates with TP53 gene mutation) and Rb protein loss by immunohistochemistry. In the study cohort, we found 11 (15%) cases of TNBC with neuroendocrine differentiation (TNBC-NED) showing positivity for one or more NE markers (synaptophysin/chromogranin/insulinoma-associated protein 1 [INSM1]). We also identified one separate small cell neuroendocrine carcinoma. Histologic types for these 11 TNBC-NED cases were as follows: 8 invasive ductal carcinoma (IDC) not otherwise specified (NOS), 2 IDC with apocrine features, 1 IDC with solid papillary features. INSM1 had the highest positivity and was seen in all 11 carcinomas. Seven (64%) cases showed p53 aberrant staining, 6 (55%) had Rb protein loss, while 6 (55%) had p53/Rb co-aberrant staining/protein loss. TNBC-NED was associated with Rb protein loss (p < 0.001), as well as p53/Rb co-aberrant staining/protein loss (p < 0.001). In 61 cases negative for NE markers, 37 (61%) showed p53 aberrant staining, while 5 (8%) had Rb protein loss. We also analyzed genomic and transcriptomic data from The Cancer Genome Atlas (TCGA) PanCancer Atlas of 171 basal/TNBC patients. Transcriptomic analysis revealed mRNA expression of RB1 to be correlated negatively with SYN1 mRNA expression (p = 0.0400) and INSM1 mRNA expression (p = 0.0106) in this cohort. We would like to highlight the importance of these findings. TNBC-NED is currently diagnosed as TNBC, and although it overlaps morphologically with TNBC without NED, the unique p53/Rb signature highlights a genetic overlap with NE carcinomas of the breast.

INTRODUCTION/BACKGROUND:Breast cancers are complex ecosystem like networks of malignant cells and their associated microenvironment. Applications for machine intelligence and the tumoral microenvironment are expanding frontiers in pathology. Previously, computational approaches have been developed to quantify and spatially analyze immune cells, proportionate stroma, and detect tumor budding. Little work has been done to analyze different types of tumor-associated stromata both quantitatively and computationally in relation to clinical endpoints. METHODS:We aimed to quantify stromal features from whole slide images (WSI) including stromata (myxoid, collagenous, immune) and tumoral components and combined them with traditional clinical and pathologic parameters in 120 triple-negative breast cancer (TNBC) patients treated with neoadjuvant chemotherapy (NAC) to predict pathologic complete response (pCR) and poor clinical outcomes. RESULTS:High collagenous stroma on WSI was best associated with lower rates of pCR, while combined high proportionated stroma (myxoid, collagenous, and immune) most optimally predicted worse clinical survival outcomes. When combining clinical, pathologic, and WSI features, Receiver Operator Characteristics (ROC) curves for LASSO features was up to 0.67 for pCR and 0.77 for poor outcomes. CONCLUSION/CONCLUSIONS:The techniques demonstrated in the present study can be performed with appropriate quality assurance. Future trials are needed to demonstrate whether coupling applications for machine intelligence, inclusive of the tumor mesenchyme, can improve outcomes prediction for patients with breast cancer.

Mismatch repair (MMR) alterations are important prognostic and predictive biomarkers in a variety of cancer subtypes, including colorectal and endometrial. However, in breast cancer (BC), the distinction and clinical significance of MMR are largely unknown. This may be due in part to the fact that genetic alterations in MMR genes are rare and only seen to occur in around 3% of BCs. In the present study, we analyzed TCGA data using a multi-sample protein-protein interaction (PPI) analysis tool, Proteinarium, and showed a distinct separation between specific MMR-deficient and -intact networks in a cohort of 994 BC patients. In the PPI networks specific to MMR deficiency, highly connected clusters of histone genes were identified. We also found the distribution of MMR-deficient BC to be more prevalent in HER2-enriched and triple-negative (TN) BC subtypes compared to luminal BCs. We recommend defining MMR-deficient BC by next-generation sequencing (NGS) when any somatic mutation is detected in one of the seven MMR genes.