Comprehensive Genomic Profiling of NF2-Mutated Kidney Tumors Reveals Potential Targets for Therapy.

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.

"Growing fibroadenoma": Are there clinical and pathological features predicting a phyllodes tumor on surgical excision?

In cases of growth of FA on imaging, core needle biopsies (CNB) are often performed to rule out phyllodes tumor (PT). We aim to focus on "growing FAs" and to identify clinical and histopathologic features that are likely to predict a PT on excision. Thirty-four FAs with radiologic documentation of growth were included. Various clinical and pathological features such as age, body mass index (BMI), lesion size, and growth rate were recorded. On excision, 17 cases (50 %) were FAs, whereas 16 (47 %) were re-classified as benign PT despite only 19 % being suspicious for PT on CNB. PT patients were older (mean age 42.6) than those with FAs (mean age 28.2), p = 0.0002. All false negative cases demonstrated intracanalicular growth. Mitotic rate was the most significant histologic feature in PT on excision compared to others, such as lesion circumscription and stromal cellularity. Recognition and careful counting of mitotic rate, especially with intracanalicular patterns in growing FAs, can potentially prevent missing a PT on CNB. In patients with "growing FAs" who are ≥40 years of age, excision may be recommended due to the high likelihood of PT diagnosis on excision and high false negative rate on CNB.

MMR Deficiency Defines Distinct Molecular Subtype of Breast Cancer with Histone Proteomic Networks.

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.

Androgen Receptor Immunohistochemical Expression in Undifferentiated/Dedifferentiated Endometrial Carcinoma.

Uterine undifferentiated (UC)/dedifferentiated (DEAC) carcinomas are rare malignant neoplasms. They tend to pursue an aggressive clinical course with an advanced stage at presentation. It has been found that androgen receptor (AR) might play a role as a prognostic and therapeutic marker in endometrial carcinoma. However, its expression in UC/DEAC has not been investigated. Herein, the aim of this study was to evaluate the expression of AR along with estrogen receptor (ER), progestin receptor (PR), and HER2 in UC/DEAC and also in other subtypes of high-grade endometrial carcinomas. Review of our pathology database over the period of 2011 to 2019 identified 16 UC/DEAC cases (N=16). We also randomly selected other high-grade endometrial carcinomas including FIGO 3 endometrioid carcinoma (N=9), serous carcinoma (N=8), clear cell carcinoma (N=12) and carcinosarcoma (N=10) for comparison. Immunohistochemical stains for AR, ER, PR, and HER2 were performed on all 55 cases. The protein expression was evaluated both quantitatively and qualitatively. In DEAC cases both the undifferentiated component and the well-differentiated component were recorded separately. Overall, variable degrees of AR reactivity (by Allred scoring method) was present in 63% of UC/DEACs(10/16), 67% of FIGO 3 endometrioid carcinomas (6/9), 88% of serous carcinomas (7/8), 80% of carcinosarcomas (8/10), and 9% of clear cell carcinoma (1/12). AR expression was most often seen with PR (70%) or ER (60%) staining in UC/DEACs. Thirteen cases of UC/DEACs were positive for at least 1 hormone receptor. HER2 was negative in all UC/DEACs. Almost all other high-grade carcinoma cases were negative for HER2 except 20% of carcinosarcoma (2/10) and 13% of serous carcinoma (1/8) which showed 3+ HER2. Loss of AR appears to be associated with worse clinicopathologic parameters in UC/DEAC. AR is highly expressed in UC/DEAC, and in the majority of FIGO 3 endometrioid carcinomas, serous carcinomas, and carcinosarcoma. These findings suggest a potential role for androgen inhibitors in the management of patients with these tumors.

Deep learning for the classification of medical kidney disease: a pilot study for electron microscopy.

Artificial intelligence (AI) is a new frontier and often enigmatic for medical professionals. Cloud computing could open up the field of computer vision to a wider medical audience and deep learning on the cloud allows one to design, develop, train and deploy applications with ease. In the field of histopathology, the implementation of various applications in AI has been successful for whole slide images rich in biological diversity. However, the analysis of other tissue medias, including electron microscopy, is yet to be explored. The present study aims to evaluate deep learning for the classification of medical kidney disease on electron microscopy images: amyloidosis, diabetic glomerulosclerosis, membranous nephropathy, membranoproliferative glomerulonephritis (MPGN), and thin basement membrane disease (TBMD). We found good overall classification with the MedKidneyEM-v1 Classifier and when looking at normal and diseased kidneys, the average area under the curve for precision and recall was 0.841. The average area under the curve for precision and recall on the disease only cohort was 0.909. Digital pathology will shape a new era for medical kidney disease and the present study demonstrates the feasibility of deep learning for electron microscopy. Future approaches could be used by renal pathologists to improve diagnostic concordance, determine therapeutic strategies, and optimize patient outcomes in a true clinical environment.

Tumor budding in colorectal carcinoma: An institutional interobserver reliability and prognostic study of colorectal adenocarcinoma cases.

BACKGROUND: Colorectal carcinomas are one of the most commonly diagnosed malignancies. There are many prognostic factors relating to clinical course and disease progression, including tumor stage, metastasis, and tumor budding. In 2016, the International Tumor Budding Consensus Conference (ITBCC) created a system to uniformly assess tumor budding. This system includes a 3-tier system for the grading of tumor budding. In the past, there lacked uniform consensus, however the general grading practice was based on a 2-tiered system. Given that tumor budding is considered to have prognostic value, the accuracy and reproducibility of its assessment is vital. Our study aims to look at interobserver agreement in the scoring of tumor budding. DESIGN: A total of 233 cases of colorectal carcinoma diagnosed in our health system were retrospectively analyzed and routine H&E stained slides of these cases were collected. A representative slide for tumor budding was selected per case. Four investigators with different levels of experience and expertise evaluated the selected slide of each case for tumor budding. Scoring was based on the ITBCC protocol. Clinico-pathological data was collected for each case and analyzed with tumor budding scores. Tumor budding scores per individual investigator and consensus tumor budding score were compared to patient and tumor characteristics including patient survival, tumor grade, tumor stage, and lymph node status. RESULTS: Inter-observer agreement was calculated using Gwet's Agreement Coefficient (AC1) and associated 95% confidence intervals was used to compare the ratings made by 4 pathologists. Overall, there was variation among pathologists in tumor budding score (Gwet's agreement coefficient = 0.25 and 0.326 for 3-tier and 2-tier grading system, respectively). Results show higher reliability with the 2-tier system compared to the 3-tier system. Tumor stage was significantly associated with budding score for all individual investigators and the consensus value (p value < 0.001). CONCLUSION: There is low inter-observer agreement in the assessment of tumor budding in colorectal carcinoma. This suggests that it is difficult to uniformly grade tumor budding and that our classification system needs improvement. We found that the older 2-tier system (Hase et al.) results in slightly higher inter-observer agreement than the recently proposed 3-tier grading system (ITBCC, 2016), though both systems lead to suboptimal agreement. Worth noting is that observers with subspecialty GI training and more work experience had higher inter-observer agreement. Our results showed that subspecialty training tends to increase agreement more than overall work experience. In addition, our exploratory results showed that there is an association of tumor budding score to tumor stage. While increasing refinement in classification, the 3-tiered system resulted in decreased agreement in tumor budding assessment. Clearly, there is more work to be done in the identification and quantification of tumor buds.

ChatGPT and Medicine: Together We Embrace the AI Renaissance.

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.

Whole slide images as non-fungible tokens: A decentralized approach to secure, scalable data storage and access.

Background: Distributed ledger technology (DLT) enables the creation of tamper-resistant, decentralized, and secure digital ledgers. A non-fungible token (NFT) represents a record on-chain associated with a digital or physical asset, such as a whole-slide image (WSI). The InterPlanetary File System (IPFS) represents an off-chain network, hypermedia, and file sharing peer-to-peer protocol for storing and sharing data in a distributed file system. Today, we need cheaper, more efficient, highly scalable, and transparent solutions for WSI data storage and access of medical records and medical imaging data. Methods: WSIs were created from non-human tissues and H&E-stained sections were scanned on a Philips Ultrafast WSI scanner at 40× magnification objective lens (1 µm/pixel). TIFF images were stored on IPFS, while NFTs were minted on the Ethereum blockchain network in ERC-1155 standard. WSI-NFTs were stored on MetaMask and OpenSea was used to display the WSI-NFT collection. Filebase storage application programing interface (API) were used to create dedicated gateways and content delivery networks (CDN). Results: A total of 10 WSI-NFTs were minted on the Ethereum blockchain network, found on our collection "Whole Slide Images as Non-fungible Tokens Project" on Open Sea: https://opensea.io/collection/untitled-collection-126765644. WSI TIFF files ranged in size from 1.6 to 2.2 GB and were stored on IPFS and pinned on 3 separate nodes. Under optimal conditions, and using a dedicated CDN, WSI reached retrieved at speeds of over 10 mb/s, however, download speeds and WSI retrieval times varied significantly depending on the file and gateway used. Overall, the public IPFS gateway resulted in variably poorer WSI download retrieval performance compared to gateways provided by Filebase storage API. Conclusion: Whole-slide images, as the most complex and substantial data files in healthcare, demand innovative solutions. In this technical report, we identify pitfalls in IPFS, and demonstrate proof-of-concept using a 3-layer architecture for scalable, decentralized storage, and access. Optimized through dedicated gateways and CDNs, which can be effectively applied to all medical data and imaging modalities across the healthcare sector. DLT and off-chain network solutions present numerous opportunities for advancements in clinical care, education, and research. Such approaches uphold the principles of equitable healthcare data ownership, security, and democratization, and are poised to drive significant innovation.

A novel approach correlating pathologic complete response with digital pathology and radiomics in triple-negative breast cancer.

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.

Stromal grading predicts pathologic complete response and prognosis in triple-negative breast cancer.

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.

Chondrosarcoma of the thyroid cartilage: surgical management of a rare case.

Laryngeal malignancy encompasses about 1% of all cancers. Chondrosarcoma in the head and neck region represents about 0.1% of head and neck malignancies. Typical presenting symptoms relate to the anatomical location of these tumours and include dysphonia, inspiratory stridor, dysphagia, odynophagia or a neck mass. Benign and malignant cartilaginous cancers of the larynx have been described, and preoperative diagnosis can be difficult. Our report highlights the surgical management of a male patient in his 50s with chondrosarcoma of the thyroid cartilage.

Defining triple-negative breast cancer with neuroendocrine differentiation (TNBC-NED).

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.

Utility of Wnt family member 9b (Wnt9b) immunohistochemistry in the cytologic diagnosis of metastatic breast carcinoma.

Wnt family member 9b (Wnt9b) has been demonstrated as a valuable marker for breast cancer diagnosis in surgical pathology. In this study, we examined the utility of Wnt9b in diagnosing metastatic breast carcinoma in cytology samples. Cell blocks from fine needle aspirations (FNA) and fluid specimens of 96 metastatic breast carcinomas and 123 primary and metastatic non-breast neoplasms from various organ systems were evaluated by Wnt9b and GATA3 immunohistochemistry (IHC). Wnt9b and GATA3 were positive in 81.3% and 92.7% of metastatic breast carcinomas, respectively. Conversely, 93.5% and 90.0% of non-breast, non-urothelial carcinomas were negative for Wnt9b and GATA3, respectively. Wnt9b expression was positive in rare gastrointestinal, gynecological, lung, pancreas, and salivary gland tumors. All twenty-eight urothelial carcinomas were negative for Wnt9b, while twenty-six (92.9%) were positive for GATA3. Wnt9b was slightly less sensitive but more specific than GATA3 in diagnosing metastatic breast cancer in cytology samples. Particularly, Wnt9b shows higher specificity in differentiating breast and urothelial primaries. The combined use of Wnt9b and GATA3 may increase diagnostic accuracy.

In Search of Calcifications : Histologic Analysis and Diagnostic Yield of Stereotactic Core Needle Breast Biopsies.

OBJECTIVES: 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.

Whole slide image features predict pathologic complete response and poor clinical outcomes in triple-negative breast cancer.

INTRODUCTION: 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: 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.

Triple-negative Breast Carcinoma With Apocrine and Histiocytoid Features: A Clinicopathologic and Molecular Study of 18 Cases.

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.

From Immunohistochemistry to New Digital Ecosystems: A State-of-the-Art Biomarker Review for Precision Breast Cancer Medicine.

Breast cancers represent complex ecosystem-like networks of malignant cells and their associated microenvironment. Estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2) are biomarkers ubiquitous to clinical practice in evaluating prognosis and predicting response to therapy. Recent feats in breast cancer have led to a new digital era, and advanced clinical trials have resulted in a growing number of personalized therapies with corresponding biomarkers. In this state-of-the-art review, we included the latest 10-year updated recommendations for ER, PR, and HER2, along with the most salient information on tumor-infiltrating lymphocytes (TILs), Ki-67, PD-L1, and several prognostic/predictive biomarkers at genomic, transcriptomic, and proteomic levels recently developed for selection and optimization of breast cancer treatment. Looking forward, the multi-omic landscape of the tumor ecosystem could be integrated with computational findings from whole slide images and radiomics in predictive machine learning (ML) models. These are new digital ecosystems on the road to precision breast cancer medicine.

A Novel Superpixel Approach to the Tumoral Microenvironment in Colorectal Cancer.

Colorectal cancer (CRC) is the most common malignancy of the gastrointestinal tract. The stroma and the tumoral microenvironment (TME) represent ecosystem-like biological networks and are new frontiers in CRC. The present study demonstrates the use of a novel machine learning-based superpixel approach for whole slide images to unravel this biology. Findings of significance include the association of low proportionated stromal area, high immature stromal percentage, and high myxoid stromal ratio (MSR) with worse prognostic outcomes in CRC. Overall, stromal computational markers outperformed all others at predicting clinical outcomes. MSR may be able to prognosticate patients independent of pathological stage, representing an optimal way to effectively prognosticate CRC patients which circumvents the need for more extensive molecular and/or computational profiling. The superpixel approaches to the TME demonstrated here can be performed by a trained pathologist and recorded during synoptic cancer reporting with appropriate quality assurance. Future clinical trials will have the ultimate say in determining whether we can better tailor the need for adjuvant therapy in patients with CRC.

A Series of COVID-19 Cases With Findings in the Gastrointestinal and Hepatobiliary System.

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread worldwide. Most of the infected patients present with respiratory symptoms and acute lung damage. Here, we present three cases of patients with COVID-19 disease whose main clinical manifestations are gastrointestinal symptoms. In our first case, we present a COVID-19 patient with histologic findings associated with ischemic necrosis of the small bowel. In the second and third cases, we demonstrate acute cholecystitis and histology showing microvascular thrombosis. These three cases highlight the ischemic and thrombotic changes seen in the setting of COVID-19 infection without classic respiratory symptoms, with resulting severe gastrointestinal and hepatobiliary disease requiring surgical management. Although the bile or stool viral load was not tested in these patients, the small intestine and gallbladder were infected with SARS-CoV-2, most likely via the epithelial angiotensin-converting enzyme 2 (ACE2) receptor.