Utility of artificial intelligence in a binary classification of soft tissue tumors

Soft tissue tumors (STTs) pose diagnostic and therapeutic challenges due to their rarity, complexity, and morphological overlap. Accurate differentiation between benign and malignant STTs is important to set treatment directions, however, this task can be difficult. The integration of machine learning and artificial intelligence (AI) models can potentially be helpful in classifying these tumors. The aim of this study was to investigate AI and machine learning tools in the classification of STT into benign and malignant categories. This study consisted of three components: (1) Evaluation of whole-slide images (WSIs) to classify STT into benign and malignant entities. Five specialized soft tissue pathologists from different medical centers independently reviewed 100 WSIs, representing 100 different cases, with limited clinical information and no additional workup. The results showed an overall concordance rate of 70.4% compared to the reference diagnosis. (2) Identification of cell-specific parameters that can distinguish benign and malignant STT. Using an image analysis software (QuPath) and a cohort of 95 cases, several cell-specific parameters were found to be statistically significant, most notably cell count, nucleus/cell area ratio, nucleus hematoxylin density mean, and cell max caliper. (3) Evaluation of machine learning library (Scikit-learn) in differentiating benign and malignant STTs. A total of 195 STT cases (156 cases in the training group and 39 cases in the validation group) achieved approximately 70% sensitivity and specificity, and an AUC of 0.68. Our limited study suggests that the use of WSI and AI in soft tissue pathology has the potential to enhance diagnostic accuracy and identify parameters that can differentiate between benign and malignant STTs. We envision the integration of AI as a supportive tool to augment the pathologists' diagnostic capabilities.

The current state of digital cytology and artificial intelligence (AI): global survey results from the American Society of Cytopathology Digital Cytology Task Force

INTRODUCTION

The integration of whole slide imaging (WSI) and artificial intelligence (AI) with digital cytology has been growing gradually. Therefore, there is a need to evaluate the current state of digital cytology. This study aimed to determine the current landscape of digital cytology via a survey conducted as part of the American Society of Cytopathology (ASC) Digital Cytology White Paper Task Force.

MATERIALS AND METHODS

A survey with 43 questions pertaining to the current practices and experiences of WSI and AI in both surgical pathology and cytology was created. The survey was sent to members of the ASC, the International Academy of Cytology (IAC), and the Papanicolaou Society of Cytopathology (PSC). Responses were recorded and analyzed.

RESULTS

In total, 327 individuals participated in the survey, spanning a diverse array of practice settings, roles, and experiences around the globe. The majority of responses indicated there was routine scanning of surgical pathology slides (n = 134; 61%) with fewer respondents scanning cytology slides (n = 150; 46%). The primary challenge for surgical WSI is the need for faster scanning and cost minimization, whereas image quality is the top issue for cytology WSI. AI tools are not widely utilized, with only 16% of participants using AI for surgical pathology samples and 13% for cytology practice.

CONCLUSIONS

Utilization of digital pathology is limited in cytology laboratories as compared to surgical pathology. However, as more laboratories are willing to implement digital cytology in the near future, the establishment of practical clinical guidelines is needed.

Habitat escalated adaptive therapy (HEAT): a phase 2 trial utilizing radiomic habitat-directed and genomic-adjusted radiation dose (GARD) optimization for high-grade soft tissue sarcoma

BACKGROUND

Soft tissue sarcomas (STS), have significant inter- and intra-tumoral heterogeneity, with poor response to standard neoadjuvant radiotherapy (RT). Achieving a favorable pathologic response (FPR ≥ 95%) from RT is associated with improved patient outcome. Genomic adjusted radiation dose (GARD), a radiation-specific metric that quantifies the expected RT treatment effect as a function of tumor dose and genomics, proposed that STS is significantly underdosed. STS have significant radiomic heterogeneity, where radiomic habitats can delineate regions of intra-tumoral hypoxia and radioresistance. We designed a novel clinical trial, Habitat Escalated Adaptive Therapy (HEAT), utilizing radiomic habitats to identify areas of radioresistance within the tumor and targeting them with GARD-optimized doses, to improve FPR in high-grade STS.

METHODS

Phase 2 non-randomized single-arm clinical trial includes non-metastatic, resectable high-grade STS patients. Pre-treatment multiparametric MRIs (mpMRI) delineate three distinct intra-tumoral habitats based on apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE) sequences. GARD estimates that simultaneous integrated boost (SIB) doses of 70 and 60 Gy in 25 fractions to the highest and intermediate radioresistant habitats, while the remaining volume receives standard 50 Gy, would lead to a > 3 fold FPR increase to 24%. Pre-treatment CT guided biopsies of each habitat along with clip placement will be performed for pathologic evaluation, future genomic studies, and response assessment. An mpMRI taken between weeks two and three of treatment will be used for biological plan adaptation to account for tumor response, in addition to an mpMRI after the completion of radiotherapy in addition to pathologic response, toxicity, radiomic response, disease control, and survival will be evaluated as secondary endpoints. Furthermore, liquid biopsy will be performed with mpMRI for future ancillary studies.

DISCUSSION

This is the first clinical trial to test a novel genomic-based RT dose optimization (GARD) and to utilize radiomic habitats to identify and target radioresistance regions, as a strategy to improve the outcome of RT-treated STS patients. Its success could usher in a new phase in radiation oncology, integrating genomic and radiomic insights into clinical practice and trial designs, and may reveal new radiomic and genomic biomarkers, refining personalized treatment strategies for STS.

TRIAL REGISTRATION

NCT05301283.

TRIAL STATUS

The trial started recruitment on March 17, 2022.

Digital cytology part 2: artificial intelligence in cytology: a concept paper with review and recommendations from the American Society of Cytopathology Digital Cytology Task Force

Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytology laboratory. However, peer-reviewed real-world data and literature are lacking in regard to the current clinical landscape. The American Society of Cytopathology in conjunction with the International Academy of Cytology and the Digital Pathology Association established a special task force comprising 20 members with expertise and/or interest in digital cytology. The aim of the group was to investigate the feasibility of incorporating digital cytology, specifically cytology whole slide scanning and AI applications, into the workflow of the laboratory. In turn, the impact on cytopathologists, cytologists (cytotechnologists), and cytology departments were also assessed. The task force reviewed existing literature on digital cytology, conducted a worldwide survey, and held a virtual roundtable discussion on digital cytology and AI with multiple industry corporate representatives. This white paper, presented in 2 parts, summarizes the current state of digital cytology and AI practice in global cytology practice. Part 1 of the white paper is presented as a separate paper which details a review and best practice recommendations for incorporating digital cytology into practice. Part 2 of the white paper presented here provides a comprehensive review of AI in cytology practice along with best practice recommendations and legal considerations. Additionally, the cytology global survey results highlighting current AI practices by various laboratories, as well as current attitudes, are reported.

Digital cytology part 1: digital cytology implementation for practice: a concept paper with review and recommendations from the American Society of Cytopathology Digital Cytology Task Force

Digital cytology and artificial intelligence (AI) are gaining greater adoption in the cytopathology laboratory. However, peer-reviewed real-world data and literature are lacking regarding the current clinical landscape. The American Society of Cytopathology in conjunction with the International Academy of Cytology and the Digital Pathology Association established a special task force comprising 20 members with expertise and/or interest in digital cytology. The aim of the group was to investigate the feasibility of incorporating digital cytology, specifically cytology whole slide scanning and AI applications, into the workflow of the laboratory. In turn, the impact on cytopathologists, cytologists (cytotechnologists), and cytology departments were also assessed. The task force reviewed existing literature on digital cytology, conducted a worldwide survey, and held a virtual roundtable discussion on digital cytology and AI with multiple industry corporate representatives. This white paper, presented in 2 parts, summarizes the current state of digital cytology and AI practice in global cytology practice. Part 1 of the white paper presented herein is a review and offers best practice recommendations for incorporating digital cytology into practice. Part 2 of the white paper provides a comprehensive review of AI in cytology practice along with best practice recommendations and legal considerations. Additionally, the results of a global survey regarding digital cytology are highlighted.

Emerging Landscape of Targeted Therapy of Breast Cancers With Low Human Epidermal Growth Factor Receptor 2 Protein Expression

CONTEXT.—

Human epidermal growth factor receptor 2 (HER2) status in breast cancer is currently classified as negative or positive for selecting patients for anti-HER2 targeted therapy. The evolution of the HER2 status has included a new HER2-low category defined as an HER2 immunohistochemistry score of 1+ or 2+ without gene amplification. This new category opens the door to a targetable HER2-low breast cancer population for which new treatments may be effective.

OBJECTIVE.—

To review the current literature on the emerging category of breast cancers with low HER2 protein expression, including the clinical, histopathologic, and molecular features, and outline the clinical trials and best practice recommendations for identifying HER2-low-expressing breast cancers by immunohistochemistry.

DATA SOURCES.—

We conducted a literature review based on peer-reviewed original articles, review articles, regulatory communications, ongoing and past clinical trials identified through ClinicalTrials.gov, and the authors' practice experience.

CONCLUSIONS.—

The availability of new targeted therapy potentially effective for patients with breast cancers with low HER2 protein expression requires multidisciplinary recognition. In particular, pathologists need to recognize and identify this category to allow the optimal selection of patients for targeted therapy.

Recommendations for Performance Evaluation of Machine Learning in Pathology: A Concept Paper From the College of American Pathologists

CONTEXT.—

Machine learning applications in the pathology clinical domain are emerging rapidly. As decision support systems continue to mature, laboratories will increasingly need guidance to evaluate their performance in clinical practice. Currently there are no formal guidelines to assist pathology laboratories in verification and/or validation of such systems. These recommendations are being proposed for the evaluation of machine learning systems in the clinical practice of pathology.

OBJECTIVE.—

To propose recommendations for performance evaluation of in vitro diagnostic tests on patient samples that incorporate machine learning as part of the preanalytical, analytical, or postanalytical phases of the laboratory workflow. Topics described include considerations for machine learning model evaluation including risk assessment, predeployment requirements, data sourcing and curation, verification and validation, change control management, human-computer interaction, practitioner training, and competency evaluation.

DATA SOURCES.—

An expert panel performed a review of the literature, Clinical and Laboratory Standards Institute guidance, and laboratory and government regulatory frameworks.

CONCLUSIONS.—

Review of the literature and existing documents enabled the development of proposed recommendations. This white paper pertains to performance evaluation of machine learning systems intended to be implemented for clinical patient testing. Further studies with real-world clinical data are encouraged to support these proposed recommendations. Performance evaluation of machine learning models is critical to verification and/or validation of in vitro diagnostic tests using machine learning intended for clinical practice.

Stroma-Mediated Breast Cancer Cell Proliferation Indirectly Drives Chemoresistance by Accelerating Tumor Recovery between Chemotherapy Cycles

The ability of tumors to survive therapy reflects both cell-intrinsic and microenvironmental mechanisms. Across many cancers, including triple-negative breast cancer (TNBC), a high stroma/tumor ratio correlates with poor survival. In many contexts, this correlation can be explained by the direct reduction of therapy sensitivity induced by stroma-produced paracrine factors. We sought to explore whether this direct effect contributes to the link between stroma and poor responses to chemotherapies. In vitro studies with panels of TNBC cell line models and stromal isolates failed to detect a direct modulation of chemoresistance. At the same time, consistent with prior studies, fibroblast-produced secreted factors stimulated treatment-independent enhancement of tumor cell proliferation. Spatial analyses indicated that proximity to stroma is often associated with enhanced tumor cell proliferation in vivo. These observations suggested an indirect link between stroma and chemoresistance, where stroma-augmented proliferation potentiates the recovery of residual tumors between chemotherapy cycles. To evaluate this hypothesis, a spatial agent-based model of stroma impact on proliferation/death dynamics was developed that was quantitatively parameterized using inferences from histologic analyses and experimental studies. The model demonstrated that the observed enhancement of tumor cell proliferation within stroma-proximal niches could enable tumors to avoid elimination over multiple chemotherapy cycles. Therefore, this study supports the existence of an indirect mechanism of environment-mediated chemoresistance that might contribute to the negative correlation between stromal content and poor therapy outcomes.

SIGNIFICANCE

Integration of experimental research with mathematical modeling reveals an indirect microenvironmental chemoresistance mechanism by which stromal cells stimulate breast cancer cell proliferation and highlights the importance of consideration of proliferation/death dynamics. See related commentary by Wall and Echeverria, p. 3667.

Revolutionizing Digital Pathology With the Power of Generative Artificial Intelligence and Foundation Models

Digital pathology has transformed the traditional pathology practice of analyzing tissue under a microscope into a computer vision workflow. Whole-slide imaging allows pathologists to view and analyze microscopic images on a computer monitor, enabling computational pathology. By leveraging artificial intelligence (AI) and machine learning (ML), computational pathology has emerged as a promising field in recent years. Recently, task-specific AI/ML (eg, convolutional neural networks) has risen to the forefront, achieving above-human performance in many image-processing and computer vision tasks. The performance of task-specific AI/ML models depends on the availability of many annotated training datasets, which presents a rate-limiting factor for AI/ML development in pathology. Task-specific AI/ML models cannot benefit from multimodal data and lack generalization, eg, the AI models often struggle to generalize to new datasets or unseen variations in image acquisition, staining techniques, or tissue types. The 2020s are witnessing the rise of foundation models and generative AI. A foundation model is a large AI model trained using sizable data, which is later adapted (or fine-tuned) to perform different tasks using a modest amount of task-specific annotated data. These AI models provide in-context learning, can self-correct mistakes, and promptly adjust to user feedback. In this review, we provide a brief overview of recent advances in computational pathology enabled by task-specific AI, their challenges and limitations, and then introduce various foundation models. We propose to create a pathology-specific generative AI based on multimodal foundation models and present its potentially transformative role in digital pathology. We describe different use cases, delineating how it could serve as an expert companion of pathologists and help them efficiently and objectively perform routine laboratory tasks, including quantifying image analysis, generating pathology reports, diagnosis, and prognosis. We also outline the potential role that foundation models and generative AI can play in standardizing the pathology laboratory workflow, education, and training.

Validation of PRKCB Immunohistochemistry as a Biomarker for the Diagnosis of Ewing Sarcoma

Background: Ewing sarcoma (ES) can be confirmed by identifying the EWSR1-FLI1 fusion transcript. This study is to investigate whether immunostaining (IHC) of PRKCB-a protein directly regulated by EWSR1-FLI1 is a surrogate maker for diagnosing ES in routine practice. Methods: Microarray gene expression analyses were conducted. RKCB IHC was applied to 69 ES confirmed by morphology and molecular methods, and 41 non-Ewing small round cell tumors. EWSR1 rearrangement, EWSR1-FLI1 fusion or t(11;22)(q24;q12) were identified by fluorescence in situ hybridization, reverse transcriptase polymerase chain reaction, or cytogenetic analysis, respectively. Results: Gene array analyses showed significant overexpression of the PRKCB in ES. PRKCB IHC was positive in 19 cases of ES with EWSR1-FLI1 fusion, 3 cases with cytogenetic 11:22 translocation and 59 cases with EWSR1 rearrangement while negative in only one EWSR1 rearranged case. PRKCB IHC is sensitive (98%) and specific (96%) in detecting EWSR1 rearranged ES. Conclusions: PRKCB is a reliable antibody for diagnosing ES in routine practice.

Integrative diagnostics: the time is now-a report from the International Society for Strategic Studies in Radiology

Enormous recent progress in diagnostic testing can enable more accurate diagnosis and improved clinical outcomes. Yet these tests are increasingly challenging and frustrating; the volume and diversity of results may overwhelm the diagnostic acumen of even the most dedicated and experienced clinician. Because they are gathered and processed within the "silo" of each diagnostic discipline, diagnostic data are fragmented, and the electronic health record does little to synthesize new and existing data into usable information. Therefore, despite great promise, diagnoses may still be incorrect, delayed, or never made. Integrative diagnostics represents a vision for the future, wherein diagnostic data, together with clinical data from the electronic health record, are aggregated and contextualized by informatics tools to direct clinical action. Integrative diagnostics has the potential to identify correct therapies more quickly, modify treatment when appropriate, and terminate treatment when not effective, ultimately decreasing morbidity, improving outcomes, and avoiding unnecessary costs. Radiology, laboratory medicine, and pathology already play major roles in medical diagnostics. Our specialties can increase the value of our examinations by taking a holistic approach to their selection, interpretation, and application to the patient's care pathway. We have the means and rationale to incorporate integrative diagnostics into our specialties and guide its implementation in clinical practice.

Genomic Patterns of Malignant Peripheral Nerve Sheath Tumor (MPNST) Evolution Correlate with Clinical Outcome and Are Detectable in Cell-Free DNA

Malignant peripheral nerve sheath tumor (MPNST), an aggressive soft-tissue sarcoma, occurs in people with neurofibromatosis type 1 (NF1) and sporadically. Whole-genome and multiregional exome sequencing, transcriptomic, and methylation profiling of 95 tumor samples revealed the order of genomic events in tumor evolution. Following biallelic inactivation of NF1, loss of CDKN2A or TP53 with or without inactivation of polycomb repressive complex 2 (PRC2) leads to extensive somatic copy-number aberrations (SCNA). Distinct pathways of tumor evolution are associated with inactivation of PRC2 genes and H3K27 trimethylation (H3K27me3) status. Tumors with H3K27me3 loss evolve through extensive chromosomal losses followed by whole-genome doubling and chromosome 8 amplification, and show lower levels of immune cell infiltration. Retention of H3K27me3 leads to extensive genomic instability, but an immune cell-rich phenotype. Specific SCNAs detected in both tumor samples and cell-free DNA (cfDNA) act as a surrogate for H3K27me3 loss and immune infiltration, and predict prognosis.

SIGNIFICANCE

MPNST is the most common cause of death and morbidity for individuals with NF1, a relatively common tumor predisposition syndrome. Our results suggest that somatic copy-number and methylation profiling of tumor or cfDNA could serve as a biomarker for early diagnosis and to stratify patients into prognostic and treatment-related subgroups. This article is highlighted in the In This Issue feature, p. 517.

Paracrine enhancement of tumor cell proliferation provides indirect stroma-mediated chemoresistance via acceleration of tumor recovery between chemotherapy cycles

The ability of tumors to survive therapy is mediated not only by cell-intrinsic but also cell-extrinsic, microenvironmental mechanisms. Across many cancers, including triple-negative breast cancer (TNBC), a high stroma/tumor ratio correlates with poor survival. In many contexts, this correlation can be explained by the direct reduction of therapy sensitivity by stroma-produced paracrine factors through activating pro-survival signaling and stemness. We sought to explore whether this direct effect contributes to the link between stroma and poor responses to chemotherapies in TNBC. Our in vitro studies with panels of TNBC cell line models and stromal isolates failed to detect a direct modulation of chemoresistance. However, we found that fibroblasts often enhance baseline tumor cell proliferation. Consistent with this in vitro observation, we found evidence of stroma-enhanced TNBC cell proliferation in vivo , in xenograft models and patient samples. Based on these observations, we hypothesized an indirect link between stroma and chemoresistance, where stroma-augmented proliferation potentiates the recovery of residual tumors between chemotherapy cycles. To test this hypothesis, we developed a spatial agent-based model of tumor response to repeated dosing of chemotherapy. The model was quantitatively parameterized from histological analyses and experimental studies. We found that even a slight enhancement of tumor cell proliferation within stroma-proximal niches can strongly enhance the ability of tumors to survive multiple cycles of chemotherapy under biologically and clinically feasible parameters. In summary, our study uncovered a novel, indirect mechanism of chemoresistance. Further, our study highlights the limitations of short-term cytotoxicity assays in understanding chemotherapy responses and supports the integration of experimental and in silico modeling.

Integrative Diagnostics: The Time Is Now-A Report From the International Society for Strategic Studies in Radiology

Enormous recent progress in diagnostic testing can enable more accurate diagnosis and improved clinical outcomes. Yet these tests are increasingly challenging and frustrating; the volume and diversity of results may overwhelm the diagnostic acumen of even the most dedicated and experienced clinician. Because they are gathered and processed within the "silo" of each diagnostic discipline, diagnostic data are fragmented, and the electronic health record does little to synthesize new and existing data into usable information. Therefore, despite great promise, diagnoses may still be incorrect, delayed, or never made. Integrative diagnostics represents a vision for the future, wherein diagnostic data, together with clinical data from the electronic health record, are aggregated and contextualized by informatics tools to direct clinical action. Integrative diagnostics has the potential to identify correct therapies more quickly, modify treatment when appropriate, and terminate treatment when not effective, ultimately decreasing morbidity, improving outcomes, and avoiding unnecessary costs. Radiology, laboratory medicine, and pathology already play major roles in medical diagnostics. Our specialties can increase the value of our examinations by taking a holistic approach to their selection, interpretation, and application to the patient's care pathway. We have the means and rationale to incorporate integrative diagnostics into our specialties and guide its implementation in clinical practice.

NCCN Guidelines® Insights: Gastrointestinal Stromal Tumors, Version 2.2022

Gastrointestinal stromal tumors (GIST) are the most common type of soft tissue sarcoma that occur throughout the gastrointestinal tract. Most of these tumors are caused by oncogenic activating mutations in the KIT or PDGFRA genes. The NCCN Guidelines for GIST provide recommendations for the diagnosis, evaluation, treatment, and follow-up of patients with these tumors. These NCCN Guidelines Insights summarize the panel discussion behind recent important updates to the guidelines, including revised systemic therapy options for unresectable, progressive, or metastatic GIST based on mutational status, and updated recommendations for the management of GIST that develop resistance to specific tyrosine kinase inhibitors.

Assessing ROSE for adequacy of EBUS-TBNA compared with a direct-to-cell block approach as a response to the COVID-19 pandemic

Introduction:

Rapid on-site evaluation (ROSE) has been used during the endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) procedure as standard practice. Because of the COVID-19 (coronavirus disease 2019) pandemic, our institute had had to discontinue ROSE and adopt a direct-to-cell block approach. In the present study, we aimed to determine whether this change has had significant effects on the cytopathology quality.

Materials and methods:

A total of 1903 EBUS-TBNA cases from 734 patients were collected (1097 cases with ROSE for 452 patients; 806 cases without ROSE but with direct-to-cell block for 282 patients). The clinical and cytology data were analyzed using SAS, version 9.4, software to render calculated standardized residuals and a fitted multivariate generalized linear model.

Results:

On average, a biopsy from a patient with ROSE was 0.936 (=exp −0.066) times less likely to be reported as satisfactory compared with a biopsy from a patient without ROSE, although the difference was not statistically significant (P = 0.785). The inadequacy rate of EBUS-TBNA was 6.4% higher on average for cases with ROSE compared with a direct-to-cell block approach. However, this difference was also not statistically significant. The proportions of biopsies reported as diagnostic for malignancy and other were significantly different between the ROSE and no-ROSE groups with a standardized residual of 1.80 (P = 0.036) and −2.27 (P = 0.012), respectively.

Conclusions

Discontinuing ROSE and using a direct-to-cell block approach had no negative effects on cytopathology quality. This practice can be considered acceptable during the COVID-19 pandemic when social distancing and the shortage of staff and supplies have resulted in challenges to delivering quality care to cancer patients whose treatment cannot be postponed.

Proton export upregulates aerobic glycolysis

INTRODUCTION

Aggressive cancers commonly ferment glucose to lactic acid at high rates, even in the presence of oxygen. This is known as aerobic glycolysis, or the "Warburg Effect." It is widely assumed that this is a consequence of the upregulation of glycolytic enzymes. Oncogenic drivers can increase the expression of most proteins in the glycolytic pathway, including the terminal step of exporting H+ equivalents from the cytoplasm. Proton exporters maintain an alkaline cytoplasmic pH, which can enhance all glycolytic enzyme activities, even in the absence of oncogene-related expression changes. Based on this observation, we hypothesized that increased uptake and fermentative metabolism of glucose could be driven by the expulsion of H+ equivalents from the cell.

RESULTS

To test this hypothesis, we stably transfected lowly glycolytic MCF-7, U2-OS, and glycolytic HEK293 cells to express proton-exporting systems: either PMA1 (plasma membrane ATPase 1, a yeast H+-ATPase) or CA-IX (carbonic anhydrase 9). The expression of either exporter in vitro enhanced aerobic glycolysis as measured by glucose consumption, lactate production, and extracellular acidification rate. This resulted in an increased intracellular pH, and metabolomic analyses indicated that this was associated with an increased flux of all glycolytic enzymes upstream of pyruvate kinase. These cells also demonstrated increased migratory and invasive phenotypes in vitro, and these were recapitulated in vivo by more aggressive behavior, whereby the acid-producing cells formed higher-grade tumors with higher rates of metastases. Neutralizing tumor acidity with oral buffers reduced the metastatic burden.

CONCLUSIONS

Therefore, cancer cells which increase export of H+ equivalents subsequently increase intracellular alkalization, even without oncogenic driver mutations, and this is sufficient to alter cancer metabolism towards an upregulation of aerobic glycolysis, a Warburg phenotype. Overall, we have shown that the traditional understanding of cancer cells favoring glycolysis and the subsequent extracellular acidification is not always linear. Cells which can, independent of metabolism, acidify through proton exporter activity can sufficiently drive their metabolism towards glycolysis providing an important fitness advantage for survival.

Soft Tissue Sarcoma, Version 2.2022, NCCN Clinical Practice Guidelines in Oncology

Soft tissue sarcomas (STS) are rare malignancies of mesenchymal cell origin that display a heterogenous mix of clinical and pathologic characteristics. STS can develop from fat, muscle, nerves, blood vessels, and other connective tissues. The evaluation and treatment of patients with STS requires a multidisciplinary team with demonstrated expertise in the management of these tumors. The complete NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Soft Tissue Sarcoma provide recommendations for the diagnosis, evaluation, and treatment of extremity/superficial trunk/head and neck STS, as well as retroperitoneal/intra-abdominal STS, desmoid tumors, and rhabdomyosarcoma. This portion of the NCCN Guidelines discusses general principles for the diagnosis and treatment of retroperitoneal/intra-abdominal STS, outlines treatment recommendations, and reviews the evidence to support the guidelines recommendations.

Lipogenesis mediated by OGR1 regulates metabolic adaptation to acid stress in cancer cells via autophagy

Malignant tumors exhibit altered metabolism resulting in a highly acidic extracellular microenvironment. Here, we show that cytoplasmic lipid droplet (LD) accumulation, indicative of a lipogenic phenotype, is a cellular adaption to extracellular acidity. LD marker PLIN2 is strongly associated with poor overall survival in breast cancer patients. Acid-induced LD accumulation is triggered by activation of the acid-sensing G-protein-coupled receptor (GPCR) OGR1, which is expressed highly in breast tumors. OGR1 depletion inhibits acid-induced lipid accumulation, while activation by a synthetic agonist triggers LD formation. Inhibition of OGR1 downstream signaling abrogates the lipogenic phenotype, which can be rescued with OGR1 ectopic expression. OGR1-depleted cells show growth inhibition under acidic growth conditions in vitro and tumor formation in vivo. Isotope tracing shows that the source of lipid precursors is primarily autophagy-derived ketogenic amino acids. OGR1-depleted cells are defective in endoplasmic reticulum stress response and autophagy and hence fail to accumulate LDs affecting survival under acidic stress.

Validating Whole Slide Imaging Systems for Diagnostic Purposes in Pathology

CONTEXT.—

The original guideline, "Validating Whole Slide Imaging for Diagnostic Purposes in Pathology," was published in 2013 and included 12 guideline statements. The College of American Pathologists convened an expert panel to update the guideline following standards established by the National Academies of Medicine for developing trustworthy clinical practice guidelines.

OBJECTIVE.—

To assess evidence published since the release of the original guideline and provide updated recommendations for validating whole slide imaging (WSI) systems used for diagnostic purposes.

DESIGN.—

An expert panel performed a systematic review of the literature. Frozen sections, anatomic pathology specimens (biopsies, curettings, and resections), and hematopathology cases were included. Cytology cases were excluded. Using the Grading of Recommendations Assessment, Development, and Evaluation approach, the panel reassessed and updated the original guideline recommendations.

RESULTS.—

Three strong recommendations and 9 good practice statements are offered to assist laboratories with validating WSI digital pathology systems.

CONCLUSIONS.—

Systematic review of literature following release of the 2013 guideline reaffirms the use of a validation set of at least 60 cases, establishing intraobserver diagnostic concordance between WSI and glass slides and the use of a 2-week washout period between modalities. Although all discordances between WSI and glass slide diagnoses discovered during validation need to be reconciled, laboratories should be particularly concerned if their overall WSI-glass slide concordance is less than 95%.

OUP accepted manuscript

Background

Cancer of unknown primary (CUP) comprises a heterogeneous collection of malignancies that are typically associated with a poor prognosis and a lack of effective treatment options. We retrospectively evaluated the clinical utility of targeted next-generation sequencing (NGS) among CUP patients to assist with diagnosis and identify opportunities for molecularly guided therapy.

Patients and Methods

Patients with a CUP at Moffitt Cancer Center who underwent NGS between January 1, 2014 and December 31, 2019, were eligible for study inclusion. Next-generation sequencing results were assessed to determine the frequency of clinically actionable molecular alterations, and chart reviews were performed to ascertain the number of patients receiving molecularly guided therapy.

Results

Ninety-five CUP patients were identified for analysis. Next-generation sequencing testing identified options for molecularly guided therapy for 55% (n = 52) of patients. Among patients with molecularly guided therapy options, 33% (n = 17) were prescribed a molecularly guided therapy. The median overall survival for those receiving molecularly guided therapy was 23.6 months. Among the evaluable patients, the median duration of treatment for CUP patients (n = 7) receiving molecular-guided therapy as a first-line therapy was 39 weeks. The median duration of treatment for CUP patients (n = 8) treated with molecularly guided therapy in the second- or later-line setting was 13 weeks. Next-generation sequencing results were found to be suggestive of a likely primary tumor type for 15% (n = 14) of patients.

Conclusion

Next-generation sequencing results enabled the identification of treatment options in a majority of patients and assisted with the identification of a likely primary tumor type in a clinically meaningful subset of patients.

Bridging the Gap: The Critical Role of Regulatory Affairs and Clinical Affairs in the Total Product Life Cycle of Pathology Imaging Devices and Software

Manufacturers of pathology imaging devices and associated software engage regulatory affairs and clinical affairs (RACA) throughout the Total Product Life Cycle (TPLC) of regulated products. A number of manufacturers, pathologists, and end users are not familiar with how RACA involvement benefits each stage of the TPLC. RACA professionals are important contributors to product development and deployment strategies because these professionals maintain an understanding of the scientific, technical, and clinical aspects of biomedical product regulation, as well as the relevant knowledge of regulatory requirements, policies, and market trends for both local and global regulations and standards. Defining a regulatory and clinical strategy at the beginning of product design enables early evaluation of risks and provides assurance that the collected evidence supports the product's clinical claims (e.g., in a marketing application), its safe and effective use, and potential reimbursement strategies. It is recommended to involve RACA early and throughout the TPLC to assist with navigating changes in the regulatory environment and dynamic diagnostic market. Here we outline how various stakeholders can utilize RACA to navigate the nuanced landscape behind the development and use of clinical diagnostic products. Collectively, this work emphasizes the critical importance of RACA as an integral part of product development and, thereby, sustained innovation.

Quantitative Image Analysis for Tissue Biomarker Use: A White Paper From the Digital Pathology Association

Tissue biomarkers have been of increasing utility for scientific research, diagnosing disease, and treatment response prediction. There has been a steady shift away from qualitative assessment toward providing more quantitative scores for these biomarkers. The application of quantitative image analysis has thus become an indispensable tool for in-depth tissue biomarker interrogation in these contexts. This white paper reviews current technologies being employed for quantitative image analysis, their application and pitfalls, regulatory framework demands, and guidelines established for promoting their safe adoption in clinical practice.

Unusual Presentation of Widely Metastatic Extraskeletal Osteosarcoma: Case Report

Extraskeletal osteosarcoma is a highly aggressive malignant osteoid forming mesenchymal neoplasm arising from soft tissues which accounts for 1% of all soft tissue sarcomas. We report the case of a 46-year-old female with no significant past medical history presenting to an emergency department with a right lateral thigh mass following minor trauma. She was eventually found to have high grade extraskeletal osteosarcoma with rapid progression of disease resulting in patient demise. Differentiation of these lesions from alternative processes relies on specific imaging and pathologic features. Differential diagnoses include both benign and malignant etiologies such as myositis ossificans, soft tissue hemangiomas, and other malignant soft tissue neoplasms such as epithelial and synovial sarcoma.

Deep-learning and MR images to target hypoxic habitats with evofosfamide in preclinical models of sarcoma

Rationale: Hypoxic regions (habitats) within tumors are heterogeneously distributed and can be widely variant. Hypoxic habitats are generally pan-therapy resistant. For this reason, hypoxia-activated prodrugs (HAPs) have been developed to target these resistant volumes. The HAP evofosfamide (TH-302) has shown promise in preclinical and early clinical trials of sarcoma. However, in a phase III clinical trial of non-resectable soft tissue sarcomas, TH-302 did not improve survival in combination with doxorubicin (Dox), possibly due to a lack of patient stratification based on hypoxic status. Therefore, we used magnetic resonance imaging (MRI) to identify hypoxic habitats and non-invasively follow therapies response in sarcoma mouse models. Methods: We developed deep-learning (DL) models to identify hypoxia, using multiparametric MRI and co-registered histology, and monitored response to TH-302 in a patient-derived xenograft (PDX) of rhabdomyosarcoma and a syngeneic model of fibrosarcoma (radiation-induced fibrosarcoma, RIF-1). Results: A DL convolutional neural network showed strong correlations (>0.76) between the true hypoxia fraction in histology and the predicted hypoxia fraction in multiparametric MRI. TH-302 monotherapy or in combination with Dox delayed tumor growth and increased survival in the hypoxic PDX model (p<0.05), but not in the RIF-1 model, which had a lower volume of hypoxic habitats. Control studies showed that RIF-1 resistance was due to hypoxia and not other causes. Notably, PDX tumors developed resistance to TH-302 under prolonged treatment that was not due to a reduction in hypoxic volumes. Conclusion: Artificial intelligence analysis of pre-therapy MR images can predict hypoxia and subsequent response to HAPs. This approach can be used to monitor therapy response and adapt schedules to forestall the emergence of resistance.

Spontaneous cell fusions as a mechanism of parasexual recombination in tumour cell populations

The initiation and progression of cancers reflect the underlying process of somatic evolution, in which the diversification of heritable phenotypes provides a substrate for natural selection, resulting in the outgrowth of the most fit subpopulations. Although somatic evolution can tap into multiple sources of diversification, it is assumed to lack access to (para)sexual recombination-a key diversification mechanism throughout all strata of life. On the basis of observations of spontaneous fusions involving cancer cells, the reported genetic instability of polypoid cells and the precedence of fusion-mediated parasexual recombination in fungi, we asked whether cell fusions between genetically distinct cancer cells could produce parasexual recombination. Using differentially labelled tumour cells, we found evidence of low-frequency, spontaneous cell fusions between carcinoma cells in multiple cell line models of breast cancer both in vitro and in vivo. While some hybrids remained polyploid, many displayed partial ploidy reduction, generating diverse progeny with heterogeneous inheritance of parental alleles, indicative of partial recombination. Hybrid cells also displayed elevated levels of phenotypic plasticity, which may further amplify the impact of cell fusions on the diversification of phenotypic traits. Using mathematical modelling, we demonstrated that the observed rates of spontaneous somatic cell fusions may enable populations of tumour cells to amplify clonal heterogeneity, thus facilitating the exploration of larger areas of the adaptive landscape (relative to strictly asexual populations), which may substantially accelerate a tumour's ability to adapt to new selective pressures.

Artificial selection for host resistance to tumour growth and subsequent cancer cell adaptations: an evolutionary arms race

BACKGROUND

Cancer progression is governed by evolutionary dynamics in both the tumour population and its host. Since cancers die with the host, each new population of cancer cells must reinvent strategies to overcome the host's heritable defences. In contrast, host species evolve defence strategies over generations if tumour development limits procreation.

METHODS

We investigate this "evolutionary arms race" through intentional breeding of immunodeficient SCID and immunocompetent Black/6 mice to evolve increased tumour suppression. Over 10 generations, we injected Lewis lung mouse carcinoma cells [LL/2-Luc-M38] and selectively bred the two individuals with the slowest tumour growth at day 11. Their male progeny were hosts in the subsequent round.

RESULTS

The evolved SCID mice suppressed tumour growth through biomechanical restriction from increased mesenchymal proliferation, and the evolved Black/6 mice suppressed tumour growth by increasing immune-mediated killing of cancer cells. However, transcriptomic changes of multicellular tissue organisation and function genes allowed LL/2-Luc-M38 cells to adapt through increased matrix remodelling in SCID mice, and reduced angiogenesis, increased energy utilisation and accelerated proliferation in Black/6 mice.

CONCLUSION

Host species can rapidly evolve both immunologic and non-immunologic tumour defences. However, cancer cell plasticity allows effective phenotypic and population-based counter strategies.

NCCN Guidelines Insights: Soft Tissue Sarcoma, Version 1.2021

The NCCN Guidelines for Soft Tissue Sarcoma provide recommendations for the diagnosis, evaluation, treatment, and follow-up for patients with soft tissue sarcomas. These NCCN Guidelines Insights summarize the panel discussion behind recent important updates to the guidelines, including the development of a separate and distinct guideline for gastrointestinal stromal tumors (GISTs); reconception of the management of desmoid tumors; inclusion of further recommendations for the diagnosis and management of extremity/body wall, head/neck sarcomas, and retroperitoneal sarcomas; modification and addition of systemic therapy regimens for sarcoma subtypes; and revision of the principles of radiation therapy for soft tissue sarcomas.

H3F3A G34 mutation DNA sequencing and G34W immunohistochemistry analysis in 366 cases of giant cell tumors of bone and other bone tumors

H3F3A mutations and the expression of glycine 34 to tryptophan (G34W) mutants in giant cell tumors of bone (GCTBs) and other bone tumors were detected to compare H3F3A mutation types and the expression of G34W-mutant protein in order to provide a theoretical basis for using H3F3A mutations as a diagnostic and differential-diagnostic tool for GCTBs. A total of 366 bone tumor cases were investigated. The cases involved 215 men and 151 women, whose median age was 29 years (3-84). The cases included GCTB (n=180), recurrent GCTB (n=19), GCTB with lung metastasis (n=5), pediatric GCTB (n=15), primary malignant GCTB (n=5), chondroblastoma (CB, n=61), chondrosarcoma grade II (n=15), dedifferentiated chondrosarcoma (n=17), chondromyxoid fibroma (n=9), aneurysmal bone cyst (n=9), nonossifying fibroma (n=9), osteosarcoma (n=16), and undifferentiated sarcoma (n=6). Sanger DNA sequencing analysis was used to detect H3F3A mutations. Immunohistochemistry was used to assess the expression of the G34W-mutated protein in these bone tumors. DNA sequencing results revealed H3F3A mutations in 95.00% of GCTBs (171/180), including glycine 34 to tryptophan (G34W, 163/180, 90.56%), glycine 34 to leucine (G34L, 3/180, 1.67%), glycine 34 to valine (G34V, 3/180, 1.67%), and glycine 34 to arginine (G34R, 2/180, 1.11%). Recurrent GCTBs mostly had the H3F3A G34W mutation (18/19, 94.74%), and GCTBs with lung metastasis all had the H3F3A G34W mutation (5/5, 100%). Pediatric GCTBs had a mutation rate of 93.33% (14/15), including one case with G34L. Four cases of primary malignant GCTB showed the H3F3A G34W mutation (4/5, 80.00%), and the classical GCTB component and malignant component showed consistent mutation types. Immunohistochemistry showed that GCTBs harboring G34W also expressed the mutant protein in tumor cell nuclei. Furthermore, one case of GCTB and one case of recurrent GCTB showed positive G34W immunostaining results despite being negative for the genetic mutation. Other bone tumors all showed wild-type expression in both DNA sequencing and immunohistochemistry. Our large-sample DNA sequencing analysis detected four different forms of mutations in GCTBs, including three rare mutation forms. The most common mutation of H3F3A was G34W, which was in accordance with the expression of G34W in GCTBs detected by immunohistochemistry. Although DNA sequencing analysis detected rare mutation types of H3F3A, false-negative results were also present due to the small number of cells in the samples. Detection of the most common (G34W) mutant protein by immunohistochemistry was more convenient. Given the high prevalence of these driver mutations, the detection of H3F3A mutant proteins can assist in the diagnosis of GCTB and its differential diagnosis from other bone tumors.

Soft Tissue Sarcoma, Version 2.2018, NCCN Clinical Practice Guidelines in Oncology

Soft tissue sarcomas (STS) are rare solid tumors of mesenchymal cell origin that display a heterogenous mix of clinical and pathologic characteristics. STS can develop from fat, muscle, nerves, blood vessels, and other connective tissues. The evaluation and treatment of patients with STS requires a multidisciplinary team with demonstrated expertise in the management of these tumors. The complete NCCN Guidelines for STS provide recommendations for the diagnosis, evaluation, and treatment of extremity/superficial trunk/head and neck STS, as well as intra-abdominal/retroperitoneal STS, gastrointestinal stromal tumors, desmoid tumors, and rhabdomyosarcoma. This portion of the NCCN Guidelines discusses general principles for the diagnosis, staging, and treatment of STS of the extremities, superficial trunk, or head and neck; outlines treatment recommendations by disease stage; and reviews the evidence to support the guidelines recommendations.

Clinical, pathological, and genomic features of EWSR1-PATZ1 fusion sarcoma

Molecular diagnostics of sarcoma subtypes commonly involve the identification of characteristic oncogenic fusions. EWSR1-PATZ1 is a rare fusion partnering in sarcoma, with few cases reported in the literature. In the current study, a series of 11 cases of EWSR1-PATZ1 fusion positive malignancies are described. EWSR1-PATZ1-related sarcomas occur across a wide age range and have a strong predilection for chest wall primary site. Secondary driver mutations in cell-cycle genes, and in particular CDKN2A (71%), are common in EWSR1-PATZ1 sarcomas in this series. In a subset of cases, an extended clinical and histopathological review was performed, as was confirmation and characterization of the fusion breakpoint revealing a novel intronic pseudoexon sequence insertion. Unified by a shared gene fusion, EWSR1-PATZ1 sarcomas otherwise appear to exhibit divergent morphology, a polyphenotypic immunoprofile, and variable clinical behavior posing challenges for precise classification.

Quantitative Image Analysis of Human Epidermal Growth Factor Receptor 2 Immunohistochemistry for Breast Cancer: Guideline From the College of American Pathologists

CONTEXT.—

Advancements in genomic, computing, and imaging technology have spurred new opportunities to use quantitative image analysis (QIA) for diagnostic testing.

OBJECTIVE.—

To develop evidence-based recommendations to improve accuracy, precision, and reproducibility in the interpretation of human epidermal growth factor receptor 2 (HER2) immunohistochemistry (IHC) for breast cancer where QIA is used.

DESIGN.—

The College of American Pathologists (CAP) convened a panel of pathologists, histotechnologists, and computer scientists with expertise in image analysis, immunohistochemistry, quality management, and breast pathology to develop recommendations for QIA of HER2 IHC in breast cancer. A systematic review of the literature was conducted to address 5 key questions. Final recommendations were derived from strength of evidence, open comment feedback, expert panel consensus, and advisory panel review.

RESULTS.—

Eleven recommendations were drafted: 7 based on CAP laboratory accreditation requirements and 4 based on expert consensus opinions. A 3-week open comment period received 180 comments from more than 150 participants.

CONCLUSIONS.—

To improve accurate, precise, and reproducible interpretation of HER2 IHC results for breast cancer, QIA and procedures must be validated before implementation, followed by regular maintenance and ongoing evaluation of quality control and quality assurance. HER2 QIA performance, interpretation, and reporting should be supervised by pathologists with expertise in QIA.

Leiomyosarcoma of the Inferior Vena Cava with Hepatic and Pulmonary Metastases: Case Report

Sarcomas are connective tissue tumors accounting for only 1% of all adult malignancies. Leiomyosarcoma (LMS) is a sarcoma arising from smooth muscle cells, and accounts for 10-20% of all sarcomas. A subtype of LMS are those originating from the smooth muscle of blood vessels. Leiomyosarcoma of the inferior vena cava is a sarcomatous tumor, with less than 350 cases described in the literature. It carries a poor prognosis, with 5- and 10-year survival rates of 31.4% and 7.4%, respectively. We present a case of a 46-year-old female with no significant past medical history presented to the emergency department with mild abdominal pain and distention, early satiety, and weight loss for three weeks, found to have unresectable metastatic leiomyosarcoma of the inferior vena cava.

Computational pathology definitions, best practices, and recommendations for regulatory guidance: a white paper from the Digital Pathology Association

In this white paper, experts from the Digital Pathology Association (DPA) define terminology and concepts in the emerging field of computational pathology, with a focus on its application to histology images analyzed together with their associated patient data to extract information. This review offers a historical perspective and describes the potential clinical benefits from research and applications in this field, as well as significant obstacles to adoption. Best practices for implementing computational pathology workflows are presented. These include infrastructure considerations, acquisition of training data, quality assessments, as well as regulatory, ethical, and cyber-security concerns. Recommendations are provided for regulators, vendors, and computational pathology practitioners in order to facilitate progress in the field. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Validation of Fluorescence in situ Hybridization Testing of USP6 Gene Rearrangement for Diagnosis of Primary Aneurysmal Bone Cyst

GOALS

Ubiquitin specific protease 6 (USP6) gene rearrangement has been reported in approximately 70%-75% of aneurysmal bone cyst cases. We hypothesize that fluorescence in situ hybridization (FISH) testing of this marker will be useful in the pathological differentiation of primary aneurysmal bone cyst (ABC), secondary ABC, giant cell tumor of bone (GCT), and telangiectatic osteosarcoma (TOS) which are morphologically similar. This study aims to evaluate the efficacy of this test and validate it for diagnostic use.

PROCEDURES

FISH was performed in primary ABC, secondary ABC, GCT and TOS using dual color USP6 gene break apart probes. The sensitivity, specificity, positive predictive value, and negative predictive values were calculated.

RESULTS

Primary ABC demonstrates USP6 rearrangement. All secondary ABC, GCT and TOS were negative. The test sensitivity and specificity in primary ABC were 53% (9/17) and 100% (18/18), respectively. The positive predictive value and negative predictive value were 100% (9/9) and 69% (18/26), respectively.

CONCLUSION

The USP6 gene break apart detected by FISH is validated as a novel diagnostic tool for primary ABC in our laboratory. This test could be used to study the predictive value of USP6 targeted therapy for primary ABC in the near future.

Multiparametric MRI and Coregistered Histology Identify Tumor Habitats in Breast Cancer Mouse Models

It is well-recognized that solid tumors are genomically, anatomically, and physiologically heterogeneous. In general, more heterogeneous tumors have poorer outcomes, likely due to the increased probability of harboring therapy-resistant cells and regions. It is hypothesized that the genomic and physiologic heterogeneity are related, because physiologically distinct regions will exert variable selection pressures leading to the outgrowth of clones with variable genomic/proteomic profiles. To investigate this, methods must be in place to interrogate and define, at the microscopic scale, the cytotypes that exist within physiologically distinct subregions ("habitats") that are present at mesoscopic scales. MRI provides a noninvasive approach to interrogate physiologically distinct local environments, due to the biophysical principles that govern MRI signal generation. Here, we interrogate different physiologic parameters, such as perfusion, cell density, and edema, using multiparametric MRI (mpMRI). Signals from six different acquisition schema were combined voxel-by-voxel into four clusters identified using a Gaussian mixture model. These were compared with histologic and IHC characterizations of sections that were coregistered using MRI-guided 3D printed tumor molds. Specifically, we identified a specific set of MRI parameters to classify viable-normoxic, viable-hypoxic, nonviable-hypoxic, and nonviable-normoxic tissue types within orthotopic 4T1 and MDA-MB-231 breast tumors. This is the first coregistered study to show that mpMRI can be used to define physiologically distinct tumor habitats within breast tumor models. SIGNIFICANCE: This study demonstrates that noninvasive imaging metrics can be used to distinguish subregions within heterogeneous tumors with histopathologic correlation.

ADAM10 Is a Potential Novel Prognostic Biomarker for Sacral Chordoma

The ADAM (A Disintegrin and Metalloprotease) is a zinc-dependent family of transmembrane proteins upregulated in cancers. As the most frequent member, ADAM10's potential prognostic role in chordoma is unknown.

OBJECTIVE

We investigated the expression of ADAM10 protein and its prognostic value in sacral chordoma.

DESIGN

Clinical information of patients with sacral chordoma diagnosis during a 7-year period and their archived pathology were retrieved. Immunohistochemistry study of the expression of ADAM10 protein in sacral chordoma and control samples was conducted. The ADAM10 expression was correlated with the patients' clinicopathological information and analyzed by statistical methods.

RESULTS

The average age of 64 patients was 57.6 years (range, 35-83 years). Follow-up ranged from 12 to 141 months (mean, 72 months). The histological type included 47 classic, 6 chondroid, and 11 dedifferentiated chordomas. The expression level of ADAM10 was significantly correlated with the histological type (χ ²=11.345, P=0.003), metastasis (χ ²=10.149, P=0.001), overall survival (log-rank test: χ ²=8.177, P=0.004) and disease free survival (log-rank test: χ ²=6.805, P=0.009). The average survival time of patients with weak expression of ADAM10 was longer than that of strong expression.

CONCLUSION

The expression of ADAM10 protein is related to the histologic type and the prognosis of sacral chordoma.

Introduction to Digital Image Analysis in Whole-slide Imaging: A White Paper from the Digital Pathology Association

The advent of whole-slide imaging in digital pathology has brought about the advancement of computer-aided examination of tissue via digital image analysis. Digitized slides can now be easily annotated and analyzed via a variety of algorithms. This study reviews the fundamentals of tissue image analysis and aims to provide pathologists with basic information regarding the features, applications, and general workflow of these new tools. The review gives an overview of the basic categories of software solutions available, potential analysis strategies, technical considerations, and general algorithm readouts. Advantages and limitations of tissue image analysis are discussed, and emerging concepts, such as artificial intelligence and machine learning, are introduced. Finally, examples of how digital image analysis tools are currently being used in diagnostic laboratories, translational research, and drug development are discussed.

Phosphaturic mesenchymal tumor with an admixture of epithelial and mesenchymal elements in the jaws: clinicopathological and immunohistochemical analysis of 22 cases with literature review

Information on the heterogeneity of phosphaturic mesenchymal tumor, a rare entity associated with tumor-induced osteomalacia, is limited. In this retrospective analysis of 222 phosphaturic mesenchymal tumors, 22 cases exhibited mixed mesenchymal and epithelial elements, which we propose to term "phosphaturic mesenchymal tumor, mixed epithelial, and connective tissue type." Phosphaturic mesenchymal tumor of the mixed epithelial and connective tissue type showed a distinctive and significant male predominance (male:female = 2.67:1), with most patients diagnosed at <40 years old. Moreover, all tumors were mainly located in the alveolar bone with focal invasion into surrounding soft tissue and oral mucosa, which could be detected preoperatively by oral examination. The mesenchymal component, composed of spindled cells resembling fibroblasts or myofibroblasts arranged in a storiform or fascicular pattern, exhibited a less prominent vasculature and lower cellularity than the typical phosphaturic mesenchymal tumor (mixed connective tissue type). The epithelial component was typically haphazardly and diffusely distributed throughout the tumor, forming small, irregular nests resembling odontogenic epithelial nests. All cases were immunoreactive for fibroblast growth factor-23, somatostatin receptor 2A, and NSE in both components. Mostly also demonstrated positive staining for CD99 (21/22, 96%), CD56 (16/22, 73%), Bcl-2 (21/22, 96%), and D2-40 (19/22, 86%) in one or both components. S100 was positive in both components in one of seven cases. Interestingly, immunoreactivity was typically stronger and more diffuse in the epithelial than in the paired mesenchymal components. The mesenchymal component was also diffusely positive for CD68 (17/17, 100%) and showed variable focal staining for SMA (15/22, 68%) and CD34 (9/19, 47 %). These results indicate that phosphaturic mesenchymal tumor of the mixed epithelial and connective tissue type has distinctive clinicopathological characteristics and a polyimmunophenotypic profile.

Clinical Utility of Genomic Profiling in the Treatment of Advanced Sarcomas: A Single-Center Experience

Purpose

Sarcomas are a diverse group of malignant tumors that arise from soft tissues or bone. For most advanced cases, there is a substantial need for improved therapeutic options and, therefore, a desire to more precisely tailor therapy in individual cases. In this study, we review our institutional experience with next-generation sequencing (NGS)–based molecular profiling for non–GI stromal tumors sarcomas, with a focus on the clinical utility of the results.

Patients and Methods

We retrospectively analyzed results of NGS performed on tumors from 114 patients with a diagnosis of sarcoma. A chart review was conducted to review the clinical impact of NGS findings.

Results

A median of three putatively oncogenic gene alterations were identified per tumor sample (range, 0 to 19) and at least one mutation was detected in 96.7% of tumors. Fifty-six patients (49.1%) harbored a finding that was felt to be actionable after review by a molecular tumor board. Five patients (4.4%) had a diagnosis change as a result of NGS findings. In 15 patients (13.2%), therapeutic selection was influenced by NGS findings. Four of 15 (26.7%) of the NGS-influenced systemic therapies resulted in clinical benefit.

Conclusion

Putatively oncogenic mutations are readily detected in the majority of sarcomas. Genetic profiling affected the diagnosis and/or treatment approach in a sizeable minority of patients with sarcoma treated at our center. Additional study is required to determine if genetic profiling leads to improved clinical outcomes.

Abstract 2395: Acid-induced autophagic protein products are stored as adiposomes in breast cancer cells

Malignant tumors exhibit altered metabolism and consume higher levels of glucose compared to surrounding normal tissue, resulting in an acidic extracellular microenvironment. Adaptation to acidic conditions is a pre-requisite for tumor cells to survive and to out-compete the stroma into which they invade. Our previous studies demonstrated that acid adaptation is associated with survival mechanisms like chronic activation of autophagy and redistribution of the lysosomal proteins to the plasma membrane. When grown under acidic pH, breast cancer cells accumulate lipids as revealed by staining with Nile Red and perilipin 2, a protein that coats lipid droplets (adiposomes). Adiposomes are dynamic organelles that store neutral lipids surrounded by a shell of proteins and phospholipid monolayer. The lipids stored in adiposomes are produced de novo, as acid-induced lipogenic phenotype is maintained, even if cells are grown with de-lipidated serum. Fatty acid synthesis inhibition was selectively toxic under acidic conditions as compared to neutral pH and attenuated acid-induced adiposome accumulation. Using 13C isotopomer analysis, we observed a major shift in glucose metabolism from Embden Meyerhof to the Pentose Phosphate Pathway, resulting in increased production of NADPH, necessary for de novo lipid synthesis. To identify the carbon source of the lipid precursors in adiposomes, we employed 13C tracer analysis using [UL] 13C Glucose, 13C3 Leucine (labeled to steady-state) 13C2 Acetate and [UL] 13C glutamine as sources of lipids in the media. 13C label incorporation was determined by LC-MS/MS from adiposomes isolated from cells grown in media containing delipidated serum at pH 6.5. Label incorporation to glycerol backbone and acyl chains of lipids was observed when 13C glucose was used as the source. We could detect (M+1 ~6% of total) labeled 13C in triglycerides from adiposomes isolated from 13C3 leucine labeled MCF7, T47D and ZR75.1 cells. These data indicate that ketogenic amino acids arising from the autophagic breakdown of proteins are the major source of carbons in adiposomal lipids. Additionally, adiposome accumulation was significantly inhibited when cells were treated with autophagy inhibitors indicating that acid induced adiposomogenesis depends on autophagy. Further, we investigated the role of various acid-sensing GPCRs such as OGR1 and TDAG8 in transducing the acid signal. CRISPR/Cas9 mediated depletion of these receptors demonstrated that only OGR1 depletion abrogated acid induced adiposome accumulation and were defective in autophagy. In addition, acid-induced adiposomogenesis required PI3K and pAkt signaling. Hence, accumulation of adiposomes is a highly regulated metabolic process related to storing autophagic products, and appears to be important in cell survival under acidosis. This increased dependence on lipid metabolism reveals novel therapeutic vulnerabilities.

Citation Format: Smitha R. Pillai, Jonathan W. Wojtkowiak, Jonathan Nguyen, Mehdi Damaghi, Marilyn M. Bui, Timothy Garrett, Robert J. Gillies. Acid-induced autophagic protein products are stored as adiposomes in breast cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2395.

US Food and Drug Administration Approval of Whole Slide Imaging for Primary Diagnosis: A Key Milestone Is Reached and New Questions Are Raised

April 12, 2017 marked a significant day in the evolution of digital pathology in the United States, when the US Food and Drug Administration announced its approval of the Philips IntelliSite Pathology Solution for primary diagnosis in surgical pathology. Although this event is expected to facilitate more widespread adoption of whole slide imaging for clinical applications in the United States, it also raises a number of questions as to the means by which pathologists might choose to incorporate this technology into their clinical practice. This article from the College of American Pathologists Digital Pathology Committee reviews frequently asked questions on this topic and provides answers based on currently available information.

A phase-1/2 study of adenovirus-p53 transduced dendritic cell vaccine in combination with indoximod in metastatic solid tumors and invasive breast cancer

Background

Indoleamine 2, 3-dioxygenase is an enzyme that causes immunosuppression in tumors. Indoximod inhibits the indoleamine 2, 3-dioxygenase pathway and enhances immunologic responses to dendritic cell (DC) vaccines preclinically. Adenovirus p53 (Ad.p53) is used to generate DC vaccines against p53. A phase-1/2 trial of indoximod with Ad.p53-DC vaccine was conducted.

Materials and Methods

The phase-1 study combined 7 indoximod dose levels with < 6 Ad.p53-DC vaccinations every 2 weeks. Primary endpoints were maximum-tolerated dose in phase 1 and objective response in phase 2. Flow cytometry measured immune responses.

Results

Thirty-nine patients were treated. In combination with Ad.p53-DC vaccine, the maximum-tolerated dose of indoximod was 1600 mg twice daily. Attributable toxicities were grade 1–2. Best response was stable disease in 4 patients. Immunologic responses were detected in 7 out of 23 evaluable patients. Median progression-free survival was 13.3 weeks (95% confidence interval, 12.97–21.85) and median overall survival was 20.71 weeks (95% confidence interval, 25.75–46.15). Nine out of 22 patients (40%) benefitted from chemotherapy after vaccination. Median overall survival in chemotherapy responders was 69.4 weeks (30.1–122.1).

Conclusions

Indoximod 1600 mg twice daily with Ad.p53-DC was well tolerated. There may have been a chemosensitization effect. Future trials should explore combining this treatment with chemotherapy.

Soft Tissue Sarcoma, Version 2.2016, NCCN Clinical Practice Guidelines in Oncology

Soft tissue sarcomas (STS) are rare solid tumors of mesenchymal cell origin that display a heterogenous mix of clinical and pathologic characteristics. STS can develop from fat, muscle, nerves, blood vessels, and other connective tissues. The evaluation and treatment of patients with STS requires a multidisciplinary team with demonstrated expertise in the management of these tumors. The complete NCCN Guidelines for Soft Tissue Sarcoma (available at NCCN.org) provide recommendations for the diagnosis, evaluation, and treatment of extremity/superficial trunk/head and neck STS, as well as intra-abdominal/retroperitoneal STS, gastrointestinal stromal tumor, desmoid tumors, and rhabdomyosarcoma. This manuscript discusses guiding principles for the diagnosis and staging of STS and evidence for treatment modalities that include surgery, radiation, chemoradiation, chemotherapy, and targeted therapy.

Soft Tissue Tumor Immunohistochemistry Update: Illustrative Examples of Diagnostic Pearls to Avoid Pitfalls

CONTEXT

- Current 2013 World Health Organization classification of tumors of soft tissue arranges these tumors into 12 groups according to their histogenesis. Tumor behavior is classified as benign, intermediate (locally aggressive), intermediate (rarely metastasizing), and malignant. In our practice, a general approach to reaching a definitive diagnosis of soft tissue tumors is to first evaluate clinicoradiologic, histomorphologic, and cytomorphologic features of the tumor to generate some pertinent differential diagnoses. These include the potential line of histogenesis and whether the tumor is benign or malignant, and low or high grade. Although molecular/genetic testing is increasingly finding its applications in characterizing soft tissue tumors, currently immunohistochemistry still not only plays an indispensable role in defining tumor histogenesis, but also serves as a surrogate for underlining molecular/genetic alterations. Objective- To provide an overview focusing on the current concepts in the classification and diagnosis of soft tissue tumors, incorporating immunohistochemistry. This article uses examples to discuss how to use the traditional and new immunohistochemical markers for the diagnosis of soft tissue tumors. Practical diagnostic pearls, summary tables, and figures are used to show how to avoid diagnostic pitfalls.

DATA SOURCES

- Data were obtained from pertinent peer-reviewed English-language literature and the authors' first-hand experience as bone and soft tissue pathologists.

CONCLUSIONS

- -The ultimate goal for a pathologist is to render a specific diagnosis that provides diagnostic, prognostic, and therapeutic information to guide patient care. Immunohistochemistry is integral to the diagnosis and management of soft tissue tumors.