An artificial intelligence-powered PD-L1 combined positive score (CPS) analyser in urothelial carcinoma alleviating interobserver and intersite variability.

AIMS: Immune checkpoint inhibitors targeting programmed death-ligand 1 (PD-L1) have shown promising clinical outcomes in urothelial carcinoma (UC). The combined positive score (CPS) quantifies PD-L1 22C3 expression in UC, but it can vary between pathologists due to the consideration of both immune and tumour cell positivity. METHODS AND RESULTS: An artificial intelligence (AI)-powered PD-L1 CPS analyser was developed using 1,275,907 cells and 6175.42 mm2 of tissue annotated by pathologists, extracted from 400 PD-L1 22C3-stained whole slide images of UC. We validated the AI model on 543 UC PD-L1 22C3 cases collected from three institutions. There were 446 cases (82.1%) where the CPS results (CPS ≥10 or <10) were in complete agreement between three pathologists, and 486 cases (89.5%) where the AI-powered CPS results matched the consensus of two or more pathologists. In the pathologist's assessment of the CPS, statistically significant differences were noted depending on the source hospital (P = 0.003). Three pathologists reevaluated discrepancy cases with AI-powered CPS results. After using the AI as a guide and revising, the complete agreement increased to 93.9%. The AI model contributed to improving the concordance between pathologists across various factors including hospital, specimen type, pathologic T stage, histologic subtypes, and dominant PD-L1-positive cell type. In the revised results, the evaluation discordance among slides from different hospitals was mitigated. CONCLUSION: This study suggests that AI models can help pathologists to reduce discrepancies between pathologists in quantifying immunohistochemistry including PD-L1 22C3 CPS, especially when evaluating data from different institutions, such as in a telepathology setting.

Simply structured polarization-independent high efficiency multilayer dielectric gratings.

A polarization-independent multilayer dielectric diffraction grating with a low aspect ratio and high diffraction efficiency was designed and fabricated. The diffraction grating designed with a grating density of 1200 lines/mm had an aspect ratio of 0.59, mean polarization-independent diffraction efficiency in the Littrow angle of ±2.5∘, and 1030-1080 nm wavelength range of 97.2%. The designed grating was fabricated using ion assisted deposition and reactive ion etching techniques. The mean polarization-independent diffraction efficiency of the fabricated grating was 96.1%, and its standard deviation was 0.68%. The fabricated diffraction grating was irradiated with a 1064 nm cw laser, with a power density of 30kW/cm2, for 1 min to measure the temperature change before and after the laser application. It was verified that the temperature variation of the diffraction grating without heat treatment was 8.8°C, and the temperature variation after heat treatment at 400°C decreased to 2.3°C.

Genomic portrait of resectable hepatocellular carcinomas: implications of RB1 and FGF19 aberrations for patient stratification.

UNLABELLED: Hepatic resection is the most curative treatment option for early-stage hepatocellular carcinoma, but is associated with a high recurrence rate, which exceeds 50% at 5 years after surgery. Understanding the genetic basis of hepatocellular carcinoma at surgically curable stages may enable the identification of new molecular biomarkers that accurately identify patients in need of additional early therapeutic interventions. Whole exome sequencing and copy number analysis was performed on 231 hepatocellular carcinomas (72% with hepatitis B viral infection) that were classified as early-stage hepatocellular carcinomas, candidates for surgical resection. Recurrent mutations were validated by Sanger sequencing. Unsupervised genomic analyses identified an association between specific genetic aberrations and postoperative clinical outcomes. Recurrent somatic mutations were identified in nine genes, including TP53, CTNNB1, AXIN1, RPS6KA3, and RB1. Recurrent homozygous deletions in FAM123A, RB1, and CDKN2A, and high-copy amplifications in MYC, RSPO2, CCND1, and FGF19 were detected. Pathway analyses of these genes revealed aberrations in the p53, Wnt, PIK3/Ras, cell cycle, and chromatin remodeling pathways. RB1 mutations were significantly associated with cancer-specific and recurrence-free survival after resection (multivariate P = 0.038 and P = 0.012, respectively). FGF19 amplifications, known to activate Wnt signaling, were mutually exclusive with CTNNB1 and AXIN1 mutations, and significantly associated with cirrhosis (P = 0.017). CONCLUSION: RB1 mutations can be used as a prognostic molecular biomarker for resectable hepatocellular carcinoma. Further study is required to investigate the potential role of FGF19 amplification in driving hepatocarcinogenesis in patients with liver cirrhosis and to investigate the potential of anti-FGF19 treatment in these patients.

A Phase II Open-Label Randomized Clinical Trial of Preoperative Durvalumab or Durvalumab plus Tremelimumab in Resectable Head and Neck Squamous Cell Carcinoma.

PURPOSE: Clinical implications of neoadjuvant immunotherapy in patients with locally advanced but resectable head and neck squamous cell carcinoma (HNSCC) remain largely unexplored. PATIENTS AND METHODS: Patients with resectable HNSCC were randomized to receive a single dose of preoperative durvalumab (D) with or without tremelimumab (T) before resection, followed by postoperative (chemo)radiotherapy based on multidisciplinary discretion and 1-year D treatment. Artificial intelligence (AI)-powered spatial distribution analysis of tumor-infiltrating lymphocytes and high-dimensional profiling of circulating immune cells tracked dynamic intratumoral and systemic immune responses. RESULTS: Of the 48 patients enrolled (D, 24 patients; D+T, 24 patients), 45 underwent surgical resection per protocol (D, 21 patients; D+T, 24 patients). D±T had a favorable safety profile and did not delay surgery. Distant recurrence-free survival (DRFS) was significantly better in patients treated with D+T than in those treated with D monotherapy. AI-powered whole-slide image analysis demonstrated that D+T significantly reshaped the tumor microenvironment toward immune-inflamed phenotypes, in contrast with the D monotherapy or cytotoxic chemotherapy. High-dimensional profiling of circulating immune cells revealed a significant expansion of T-cell subsets characterized by proliferation and activation in response to D+T therapy, which was rare following D monotherapy. Importantly, expansion of specific clusters in CD8+ T cells and non-regulatory CD4+ T cells with activation and exhaustion programs was associated with prolonged DRFS in patients treated with D+T. CONCLUSIONS: Preoperative D±T is feasible and may benefit patients with resectable HNSCC. Distinct changes in the tumor microenvironment and circulating immune cells were induced by each treatment regimen, warranting further investigation.

Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types.

BACKGROUND: The inflamed immune phenotype (IIP), defined by enrichment of tumor-infiltrating lymphocytes (TILs) within intratumoral areas, is a promising tumor-agnostic biomarker of response to immune checkpoint inhibitor (ICI) therapy. However, it is challenging to define the IIP in an objective and reproducible manner during manual histopathologic examination. Here, we investigate artificial intelligence (AI)-based immune phenotypes capable of predicting ICI clinical outcomes in multiple solid tumor types. METHODS: Lunit SCOPE IO is a deep learning model which determines the immune phenotype of the tumor microenvironment based on TIL analysis. We evaluated the correlation between the IIP and ICI treatment outcomes in terms of objective response rates (ORR), progression-free survival (PFS), and overall survival (OS) in a cohort of 1,806 ICI-treated patients representing over 27 solid tumor types retrospectively collected from multiple institutions. RESULTS: We observed an overall IIP prevalence of 35.2% and significantly more favorable ORRs (26.3% vs 15.8%), PFS (median 5.3 vs 3.1 months, HR 0.68, 95% CI 0.61 to 0.76), and OS (median 25.3 vs 13.6 months, HR 0.66, 95% CI 0.57 to 0.75) after ICI therapy in IIP compared with non-IIP patients, respectively (p<0.001 for all comparisons). On subgroup analysis, the IIP was generally prognostic of favorable PFS across major patient subgroups, with the exception of the microsatellite unstable/mismatch repair deficient subgroup. CONCLUSION: The AI-based IIP may represent a practical, affordable, clinically actionable, and tumor-agnostic biomarker prognostic of ICI therapy response across diverse tumor types.

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes as a biomarker in locally advanced unresectable thymic epithelial neoplasm: A single-center, retrospective, longitudinal cohort study.

BACKGROUND: Thymic epithelial tumors (TET) are rare malignancies and lack well-defined biomarkers for neoadjuvant therapy. This study aimed to evaluate the clinical utility of artificial intelligence (AI)-powered tumor-infiltrating lymphocyte (TIL) analysis in TET. METHODS: Patients initially diagnosed with unresectable thymoma or thymic carcinoma who underwent neoadjuvant therapy between January 2004 and December 2021 formed our study population. Hematoxylin and eosin-stained sections from the initial biopsy and surgery were analyzed using an AI-powered spatial TIL analyzer. Intratumoral TIL (iTIL) and stromal TIL (sTIL) were quantified and their immune phenotype (IP) was identified. RESULTS: Thirty-five patients were included in this study. The proportion of patients with partial response to neoadjuvant therapy was higher in the group with nondesert IP in preneoadjuvant biopsy (63.6% vs. 17.6%, p = 0.038). A significant increase in both iTIL (median 22.18/mm2 vs. 340.69/mm2 , p < 0.001) and sTIL (median 175.19/mm2 vs. 531.02/mm2 , p = 0.004) was observed after neoadjuvant therapy. Patients with higher iTIL (>147/mm2 ) exhibited longer disease-free survival (median, 29 months vs. 12 months, p = 0.009) and overall survival (OS) (median, 62 months vs. 45 months, p = 0.002). Patients with higher sTIL (>232.1/mm2 ) exhibited longer OS (median 62 months vs. 30 months, p = 0.021). CONCLUSIONS: Nondesert IP in initial biopsy was associated with a better response to neoadjuvant therapy. Increased infiltration of both iTIL and sTIL in surgical specimens were associated with longer OS in patients with TET who underwent resection followed by neoadjuvant therapy.

Papillary thyroid cancer immune phenotypes via tumor-infiltrating lymphocyte spatial analysis.

Standard-of-care treatment options provide an excellent prognosis for papillary thyroid cancers (PTCs); however, approximately 10% of cases are advanced PTCs, resulting in less than 50% 5-year survival rates. Understanding the tumor microenvironment is essential for understanding cancer progression and investigating potential biomarkers for treatment, such as immunotherapy. Our study focused on tumor-infiltrating lymphocytes (TILs), which are the main effectors of antitumor immunity and related to the mechanism of immunotherapy. Using an artificial intelligence model, we analyzed the density of intratumoral and peritumoral TILs in the pathologic slides of The Cancer Genome Atlas PTC cohort. Tumors were classified into three immune phenotypes (IPs) based on the spatial distribution of TILs: immune-desert (48%), immune-excluded (34%), and inflamed (18%). Immune-desert IP was mostly characterized by RAS mutations, high thyroid differentiation score, and low antitumor immune response. Immune-excluded IP predominantly consisted of BRAF V600E-mutated tumors and had a higher rate of lymph node metastasis. Inflamed IP was characterized by a high antitumor immune response, as demonstrated by a high cytolytic score, immune-related cell infiltrations, expression of immunomodulatory molecules (including immunotherapy target molecules), and enrichment of immune-related pathways. This study is the first to investigate IP classification using TILs in PTC through a tissue-based approach. Each IP had unique immune and genomic profiles. Further studies are warranted to assess the predictive value of IP classification in advanced PTC patients treated with immunotherapy.

Artificial intelligence-powered spatial analysis of tumor-infiltrating lymphocytes for prediction of prognosis in resected colon cancer.

Tumor-infiltrating lymphocytes (TIL) have been suggested as an important prognostic marker in colorectal cancer, but assessment usually requires additional tissue processing and interpretational efforts. The aim of this study is to assess the clinical significance of artificial intelligence (AI)-powered spatial TIL analysis using only a hematoxylin and eosin (H&E)-stained whole-slide image (WSI) for the prediction of prognosis in stage II-III colon cancer treated with surgery and adjuvant therapy. In this retrospective study, we used Lunit SCOPE IO, an AI-powered H&E WSI analyzer, to assess intratumoral TIL (iTIL) and tumor-related stromal TIL (sTIL) densities from WSIs of 289 patients. The patients with confirmed recurrences had significantly lower sTIL densities (mean sTIL density 630.2/mm2 in cases with confirmed recurrence vs. 1021.3/mm2 in no recurrence, p < 0.001). Additionally, significantly higher recurrence rates were observed in patients having sTIL or iTIL in the lower quartile groups. Risk groups defined as high-risk (both iTIL and sTIL in the lowest quartile groups), low-risk (sTIL higher than the median), or intermediate-risk (not high- or low-risk) were predictive of recurrence and were independently associated with clinical outcomes after adjusting for other clinical factors. AI-powered TIL analysis can provide prognostic information in stage II/III colon cancer in a practical manner.

A high-resolution temporal atlas of the SARS-CoV-2 translatome and transcriptome.

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which infected >200 million people resulting in >4 million deaths. However, temporal landscape of the SARS-CoV-2 translatome and its impact on the human genome remain unexplored. Here, we report a high-resolution atlas of the translatome and transcriptome of SARS-CoV-2 for various time points after infecting human cells. Intriguingly, substantial amount of SARS-CoV-2 translation initiates at a novel translation initiation site (TIS) located in the leader sequence, termed TIS-L. Since TIS-L is included in all the genomic and subgenomic RNAs, the SARS-CoV-2 translatome may be regulated by a sophisticated interplay between TIS-L and downstream TISs. TIS-L functions as a strong translation enhancer for ORF S, and as translation suppressors for most of the other ORFs. Our global temporal atlas provides compelling insight into unique regulation of the SARS-CoV-2 translatome and helps comprehensively evaluate its impact on the human genome.

The regulatory impact of RNA-binding proteins on microRNA targeting.

Argonaute is the primary mediator of metazoan miRNA targeting (MT). Among the currently identified >1,500 human RNA-binding proteins (RBPs), there are only a handful of RBPs known to enhance MT and several others reported to suppress MT, leaving the global impact of RBPs on MT elusive. In this study, we have systematically analyzed transcriptome-wide binding sites for 150 human RBPs and evaluated the quantitative effect of individual RBPs on MT efficacy. In contrast to previous studies, we show that most RBPs significantly affect MT and that all of those MT-regulating RBPs function as MT enhancers rather than suppressors, by making the local secondary structure of the target site accessible to Argonaute. Our findings illuminate the unappreciated regulatory impact of human RBPs on MT, and as these RBPs may play key roles in the gene regulatory network governed by metazoan miRNAs, MT should be understood in the context of co-regulating RBPs.

An origami-inspired, self-locking robotic arm that can be folded flat.

A foldable arm is one of the practical applications of folding. It can help mobile robots and unmanned aerial vehicles (UAVs) overcome access issues by allowing them to reach into confined spaces. The origami-inspired design enables a foldable structure to be lightweight, compact, and scalable while maintaining its kinematic behavior. However, the lack of structural stiffness has been a major limitation in the practical use of origami-inspired designs. Resolving this obstacle without losing the inherent advantages of origami is a challenge. We propose a solution by implementing a simple stiffening mechanism that uses an origami principle of perpendicular folding. The simplicity of the stiffening mechanism enables an actuation system to drive shape and stiffness changes with only a single electric motor. Our results show that this design was effective for a foldable arm and allowed a UAV to perform a variety of tasks in a confined space.

General rules for functional microRNA targeting.

The functional rules for microRNA (miRNA) targeting remain controversial despite their biological importance because only a small fraction of distinct interactions, called site types, have been examined among an astronomical number of site types that can occur between miRNAs and their target mRNAs. To systematically discover functional site types and to evaluate the contradicting rules reported previously, we used large-scale transcriptome data and statistically examined whether each of approximately 2 billion site types is enriched in differentially downregulated mRNAs responding to overexpressed miRNAs. Accordingly, we identified seven non-canonical functional site types, most of which are novel, in addition to four canonical site types, while also removing numerous false positives reported by previous studies. Extensive experimental validation and significantly elevated 3' UTR sequence conservation indicate that these non-canonical site types may have biologically relevant roles. Our expanded catalog of functional site types suggests that the gene regulatory network controlled by miRNAs may be far more complex than currently understood.

Genomic Alterations in the RB Pathway Indicate Prognostic Outcomes of Early-Stage Lung Adenocarcinoma.

PURPOSE: To better understand the complete genomic architecture of lung adenocarcinoma. EXPERIMENTAL DESIGN: We used array experiments to determine copy number variations and sequenced the complete exomes of the 247 lung adenocarcinoma tumor samples along with matched normal cells obtained from the same patients. Fully annotated clinical data were also available, providing an unprecedented opportunity to assess the impact of genomic alterations on clinical outcomes. RESULTS: We discovered that genomic alternations in the RB pathway are associated with significantly shorter disease-free survival in early-stage lung adenocarcinoma patients. This association was also observed in our independent validation cohort. The current treatment guidelines for early-stage lung adenocarcinoma patients recommend follow-up without adjuvant therapy after complete resection, except for high-risk patients. However, our findings raise the interesting possibility that additional clinical interventions might provide medical benefits to early-stage lung adenocarcinoma patients with genomic alterations in the RB pathway. When examining the association between genomic mutation and histologic subtype, we uncovered the characteristic genomic signatures of various histologic subtypes. Notably, the solid and the micropapillary subtypes demonstrated great diversity in the mutated genes, while the mucinous subtype exhibited the most unique landscape. This suggests that a more tailored therapeutic approach should be used to treat patients with lung adenocarcinoma. CONCLUSIONS: Our analysis of the genomic and clinical data for 247 lung adenocarcinomas should help provide a more comprehensive genomic portrait of lung adenocarcinoma, define molecular signatures of lung adenocarcinoma subtypes, and lead to the discovery of useful prognostic markers that could be used in personalized treatments for early-stage lung adenocarcinoma patients.