OBJECTIVE

Tumor gene expression profiling (GEP) can be used to predict recurrence risk and the potential benefit of breast cancer treatment. Adoption of GEP among privately insured patients has not been well studied. Our objectives were to characterize trends in GEP use and to evaluate per-use patient and health plan payments from 2006 to 2012.

METHODS

We used Truven Health Analytics MarketScan administrative claims database to examine GEP testing among women with breast cancer from 2006 to 2012 (N = 154,883). We estimated trends in the proportion of women who received GEP using segmented regression. We summarized average reimbursement for GEP, including insurer payments and patient out-of-pocket payments.

RESULTS

Overall, 18,575 women received GEP. The average age was 53.6 years, and most were enrolled in a preferred provider organization health plan. The adjusted proportion of women with breast cancer who received GEP grew from 2.2% in 2006 to 18.8% in 2012 (adjusted risk ratio, 8.4; 95% CI, 7.6 to 9.3). Out-of-pocket costs to the patient ranged from $0 to $4,752. Most patients paid nothing for GEP (median, $0; interquartile ratio, $4). Mean patient out-of-pocket costs were $175 (standard deviation [SD], $484). Private-insurer reimbursed amounts for GEP increased annually from an average of $3,125 (SD, $1,523) in 2006 to $3,680 (SD, $835) by 2012.

CONCLUSIONS

GEP has rapidly diffused into clinical practice. Reimbursements by insurers have increased slowly, and average out-of-pocket costs to patients have decreased, seemingly driven by improved coverage for testing over time. As more genetic tests become available, it will be important to understand how these technologies will affect cancer care costs across the US health care system.

BACKGROUND

Granulin epithelin precursor (GEP) is reported to function as a growth factor stimulating proliferation and migration, and conferring chemoresistance in many cancer types. However, the expression and functional roles of GEP in colorectal cancer (CRC) remain elusive. The aim of this study was thus to investigate the clinical significance of GEP in CRC and reveal the molecular mechanism of GEP in CRC initiation and progression.

METHODS

The mRNA expression of GEP in CRC cell lines were detected by qRT-PCR. The GEP protein expression was validated by immunohistochemistry in tissue microarray (TMA) including 190 CRC patient samples. The clinicopathological correlation analysis were achieved by GEP expression on TMA. Functional roles of GEP were determined by MTT proliferation, monolayer colony formation, cell invasion and migration and in vivo studies through siRNA/shRNA mediated knockdown assays. The cancer signaling pathway identification was acquired by flow cytometry, western blot and luciferase activity assays.

RESULTS

The mRNA expression of GEP in CRC was significantly higher than it in normal colon tissues. GEP protein was predominantly localized in the cytoplasm and most of the CRC cases demonstrated abundant GEP protein compared with non-tumorous tissues. GEP overexpression was associated with non-rectal location, advanced AJCC stage, regional lymph node and distant metastasis. By Kaplan-Meier survival analysis, GEP abundance served as a prognostic marker for worse survival in CRC patients. GEP knockdown exhibited anti-cancer effect such as inhibiting cell proliferation, monolayer colony formation, cell invasion and migration in DLD-1 and HCT 116 cells and decelerating xenograft formation in nude mice. siGEP also induced G1 cell cycle arrest and apoptosis. Luciferase activity assays further demonstrated GEP activation was involved in MAPK/ERK signaling pathway.

CONCLUSIONS

In summary, we compressively delineate the oncogenic role of GEP in colorectal tumorigenesis by activating MAPK/ERK signaling pathway. GEP might serve as a useful prognostic biomarker and therapeutic target for CRC.

UNASSIGNED

Large-scale whole-genome sequencing dataset-based studies are becoming increasingly common in pathogen surveillance and outbreak investigations. A highly discriminative and time-efficient bioinformatics tool is needed to transform large amounts of sequencing data into usable biological information. To replace the intuitive, yet inefficient, way of gene-by-gene allele calling algorithm, a new algorithm using genome-by-genome approach was developed.

UNASSIGNED

Tests showed that the program equipped with the new algorithm achieved significant improvements in allele calling efficiency compared to a conventional gene-by-gene approach. The new program, Fast-GeP, rendered a fast and easy way to infer high-resolution genealogical relationships between bacterial isolates using whole-genome sequencing data.

UNASSIGNED

FAST-GeP is freely available from: https://github.com/jizhang-nz/fast-GeP.

UNASSIGNED

Supplementary data are available at Bioinformatics online.

During evolution, proteins containing newly emerged domains and the increasing proportion of multidomain proteins in the full genome-encoded proteome (GEP) have substantially contributed to increasing biological complexity. However, it is not known how these two potential structural factors are preferentially utilized at given physiological states. Here, we classified proteins according to domain number and domain age and explored the general trends across species for the utilization of proteins from GEP to various certain-state proteomes (CSPs, i.e., all the proteins expressed at certain physiological states). We found that multidomain proteins or only older domain-containing proteins are significantly overrepresented in CSPs compared with GEP, which is a trend that is stronger in multicellular organisms than in unicellular organisms. Interestingly, the strengths of overrepresentation decreased during evolution of multicellular eukaryotes. When comparing across CSPs, we found that multidomain proteins are more overrepresented in complex tissues than in simpler ones, whereas no difference among proteins with domains of different ages is evident between complex and simple tissues. Thus, biological complexity under certain conditions is more significantly realized by diverse domain organization than by the emergence of new types of domain. In addition, we found that multidomain or only older domain-containing proteins tend to evolve slowly and generally are under stronger purifying selection, which may partly result from their general overrepresentation trends in CSPs.

Loss of heterozygosity (LOH) for markers on X chromosome are associated with malignancy in endocrine tumors of the stomach and pancreas. The aim of this work is to investigate low-grade, well-differentiated endocrine carcinomas (WDEC) vs high-grade, poorly differentiated endocrine carcinomas (PDEC) of the gastroenteropancreatic (GEP) tract for common deletion regions on X chromosome. We performed a comparative allelotyping analysis with 24 highly polymorphic markers for the X chromosome in 12 WDECs and 5 PDECs. Overall, the LOH frequency in all informative loci investigated was 59% in primary and 61% in metastasis, with a significantly higher rate in PDECs than in WDECs (p<0.015 for primary and p<0.00005 for metastasis). In both WDECs and PDECs, the small Xq25 region as defined by DXS8059, DXS8098, and DXS8009 markers showed higher LOH rate as compared to the rest of the chromosome markers (p<0.04). In addition, LOH was very frequently elevated also in DXS294 and in DXS102 loci mapping the chromosomal region Xq26. In no instances differences were found between primary tumors and metastases. Methylation analysis revealed that Xq25 loss preferentially occurred on the inactive X chromosome, a feature in agreement with findings from other human cancers suggesting escape of tumor suppressor genes to X chromosome inactivation at this region. Overall, our data indicate that the two chromosomal regions, Xq25 and Xq26, may participate to the malignant progression of GEP endocrine carcinomas.

Recent studies have shown that the gip2 and gep oncogenes defined by the α-subunits of Gi2 and G12 family of G proteins, namely Gαi2 and Gα12/13, stimulate oncogenic signaling pathways in cancer cells including those derived from ovarian cancer. However, the critical α-subunit involved in ovarian cancer growth and progression in vivo remains to be identified. Using SKOV3 cells in which the expressions of individual Gα-subunits were silenced, we demonstrate that the silencing of Gα12 and Gα13 drastically attenuated serum- or lysophosphatidic acid-stimulated proliferation. In contrast, the invasive migration of these cells were reduced only by the silencing of Gαi2 or Gα13. Analyses of the xenograft tumors derived from these Gα-silenced cells indicated that only the silencing of Gα13 drastically reduced xenograft tumor growth and prolonged the survival of the mice. Similar, but albeit reduced, effect was seen with the silencing of Gα12. On the contrary, the silencing of Gαi2 or Gαq failed to exert such effect. Thus, our studies establish for the first time that Gα12/13, the putative gep oncogenes, are the determinant α-subunits involved in ovarian cancer growth in vivo and their increased oncogenicity can be correlated with its ability to stimulate both proliferation and invasive migration.

Neuroendocrine differentiation in breast carcinomas has been a matter of discussion since it was first described almost 60 years ago. Indeed, so-called neuroendocrine neoplasms of the breast (Br-NENs) are a less well-defined group of neoplasms than analogous entities in other anatomic sites, such as the lung and the gastroenteropancreatic (GEP) tract. Pure neuroendocrine phenotype is extremely rare, whereas the expression of neuroendocrine markers in usual breast carcinomas, both of special and of non-special type, without evident neuroendocrine morphology, is more common. In this context, the diagnostic criteria and the classification scheme for Br-NENs have been continuously changing over time and real consensus on this topic is still lacking, despite the recent publication of the 5th edition of the WHO classification of breast tumors. In this review, we will recapitulate the evolution of the concept of Br-NEN; revise the available knowledge on their morphological, molecular, and clinical features; and critically discuss the current classification scheme.

Keywords: Breast; Neuroendocrine carcinoma; Neuroendocrine differentiation; Neuroendocrine neoplasms; Neuroendocrine tumor; WHO classification.

The genome of multiple myeloma (MM) cells is extremely unstable, characterized by a complex combination of structure and numerical abnormalities. It seems that there are several "myeloma subgroups" which differ in expression profile, clinical manifestations, prognoses and treatment response. In our previous work, the list of 35 candidate genes with a known role in carcinogenesis and associated with centrosome structure/function was used as a display of molecular heterogeneity with an impact in myeloma pathogenesis. The current study was devoted to establish a risk stratification model based on the aforementioned candidate genes.

A total of 151 patients were included in this study. CD138+ cells were separated by magnetic-activated cell sorting (MACS). Gene expression profiling (GEP) and Interphase FISH with cytoplasmic immunoglobulin light chain staining (cIg FISH) were performed on plasma cells (PCs). All statistical analyses were performed using freeware R and its additional packages. Training and validation cohort includes 73 and 78 patients, respectively.

We have finally established a model that includes 12 selected genes (centrosome associated gene pattern, CAGP) which appears to be an independent prognostic factor for MM stratification. We have shown that the new CAGP model can sub-stratify prognosis in patients without TP53 loss as well as in IMWG high risk patients' group.

We assume that newly established risk stratification model complements the current prognostic panel used in multiple myeloma and refines the classification of patients in relation to the disease risks. This approach can be used independently as well as in combination with other factors.

As forests age, their structure and productivity change, yet in some cases, annual rates of water loss remain unchanged. To identify mechanisms that might explain such observations, and to determine if widely different age classes of forests differ functionally, we examined young (Y, approximately 25 years), mature (M, approximately 90 years) and old (O, approximately 250 years) ponderosa pine (Pinus ponderosa Dougl. ex P. Laws.) stands growing in a drought-prone region of central Oregon. Although the stands differed in tree leaf area index (LAIT) (Y = 0.9, M = 2.8, O = 2.1), cumulative tree transpiration measured by sap flow did not differ substantially during the growing season (100-112 mm). Yet when water was readily available, transpiration per unit leaf area of the youngest trees was about three times that of M trees and five times that of O trees. These patterns resulted from a nearly sixfold difference in leaf specific conductance (KL) between the youngest and oldest trees. At the time of maximum transpiration in the Y stand in May-June, gross carbon uptake (gross ecosystem production, GEP) was similar for Y and O stands despite an almost twofold difference in stand leaf area index (LAIS). However, the higher rate of water use by Y trees was not sustainable in the drought-prone environment, and between spring and late summer, KL of Y trees declined fivefold compared with a nearly twofold decline for M trees and a < 30% reduction in O trees. Because the Y stand contained a significant shrub understory and more exposed soil, there was no appreciable difference in mean daily latent energy fluxes between the Y stand and the older stands as measured by the eddy-covariance technique. These patterns resulted in 60 to 85% higher seasonal GEP and 55 to 65% higher water-use efficiency at the M and O stands compared with the Y stand.

High-grade gastroenteropancreatic neuroendocrine neoplasms (GEP-NEN) are classified according to morphology as well differentiated neuroendocrine tumours (NET) G3 or poorly differentiated neuroendocrine carcinomas (NEC). Little data exist concerning which morphological criteria this subdivision should be based on. Uncertainty exists if the NEC group should be further subdivided according to proliferation rate. Clinical data on NET G3 and NEC with a lower Ki-67 range are limited. 213 patients with high-grade GEP-NEN (Ki-67>20%) were included from the Nordic NEC Registries. Four experienced NET pathologists re-evaluated the cases to develop the best morphological criteria to separate NET G3 from NEC, assuming longer survival in NET G3. Organoid growth pattern, capillary network in direct contact to tumour cells and absence of desmoplastic stroma were found to best separate NET G3 from NEC. Of 196 patients with metastatic disease, NET G3 was found in 12.3%, NEC with a Ki-67<55% (NEC <55) in 29.6%, and NEC with a Ki-67≥55% (NEC ≥55) in 56.6%. Only in 1.5% the morphology was ambiguous. Of 164 patients receiving 1-line chemotherapy, 88% received platinum/etoposide treatment. Response-rate was higher for NEC ≥55 (44%) compared to NEC <55 (25%) and NET G3 (24%) (P=0.025 and P=0.026). Median progression free survival was 5 months for all groups. Median overall survival was 33 months for NET G3 compared to 11 months for both NEC <55 and NEC ≥55 (P=0.004 and 0.003).

BACKGROUND

Meningioma is the most common primary brain tumor and has a variable risk of local recurrence. While World Health Organization (WHO) grade generally correlates with recurrence, there is substantial within-grade variation of recurrence risk. Current risk stratification does not accurately predict which patients are likely to benefit from adjuvant radiation therapy (RT). We hypothesized that tumors at risk for recurrence have unique gene expression profiles (GEP) that could better select patients for adjuvant RT.

METHODS

We developed a recurrence predictor by machine learning modeling using a training/validation approach.

RESULTS

Three publicly available AffymetrixU133 gene expression datasets (GSE9438, GSE16581, GSE43290) combining 127 primary, non-treated meningiomas of all grades served as the training set. Unsupervised variable selection was used to identify an 18-gene GEP model (18-GEP) that separated recurrences. This model was validated on 62 primary, non-treated cases with similar grade and clinical variable distribution as the training set. When applied to the validation set, 18-GEP separated recurrences with a misclassification error rate of 0.25 (log-rank p=0.0003). 18-GEP was predictive for tumor recurrence [p=0.0008, HR=4.61, 95%CI=1.89-11.23)] and was predictive after adjustment for WHO grade, mitotic index, sex, tumor location, and Simpson grade [p=0.0311, HR=9.28, 95%CI=(1.22-70.29)]. The expression signature included genes encoding proteins involved in normal embryonic development, cell proliferation, tumor growth and invasion (FGF9, SEMA3C, EDNRA), angiogenesis (angiopoietin-2), cell cycle regulation (CDKN1A), membrane signaling (tetraspanin-7, caveolin-2), WNT-pathway inhibitors (DKK3), complement system (C1QA) and neurotransmitter regulation (SLC1A3, Secretogranin-II).

CONCLUSIONS

18-GEP accurately stratifies patients with meningioma by recurrence risk having the potential to guide the use of adjuvant RT.

The multiple endocrine neoplasia type 1 syndrome (MEN1) natural history is poorly evaluated, and few single-institution experiences about hereditary gastroenteropancreatic neuroendocrine tumors (GEP-NET) are reported. Our purpose is to analyze the role of GEP-NET in MEN1-related death, as well as the behavior of these lesions during follow-up.

The study population consists of 77 patients diagnosed with MEN1 GEP-NET, regularly followed up since 1990. Extensive clinical data were prospectively recorded. Statistical analysis was performed both on the whole population of 77 patients and on two subgroups including patients who, during the long lasting study period, underwent GEP-NET surgery (50 pts) and who did not (27 pts), respectively.

Twenty-five males (32.5%) and 52 females (67.5%) were enrolled. Sixty-four patients had MEN1 family history (83.1%), and genetic mutation was detected in 67 cases (87%). The mean age at GEP-NET diagnosis was 41.4 years (SD = 13.6); 16 patients (20.8%) had GEP-NET diagnosed before age 30 and 12 cases (15.6%) before 1996. The mean interval time between MEN1 diagnosis and GEP-NET detection was 5.7 years (range -11/37; SD = 8.1 years). Overall, the mean follow-up time from MEN1 diagnosis was 15.8 years (SD = 9.7 years) and from GEP-NET diagnosis was 9.6 years (SD = 6.9 years). Gastrinoma was the most frequent functioning GEP-NET and pancreatoduodenectomy the most adopted surgery. GEP-NET progression affected 12 patients within the non-surgical group, while 18 subjects developed progression after surgery.

Our single-center data provide information on epidemiologic, clinical and pathological features of GEP-NET in MEN1 making possible to clarify their natural history.

Importance: Use of prognostic gene expression profile (GEP) testing in cutaneous melanoma (CM) is rising despite a lack of endorsement as standard of care.

Objective: To develop guidelines within the national Melanoma Prevention Working Group (MPWG) on integration of GEP testing into the management of patients with CM, including (1) review of published data using GEP tests, (2) definition of acceptable performance criteria, (3) current recommendations for use of GEP testing in clinical practice, and (4) considerations for future studies.

Evidence review: The MPWG members and other international melanoma specialists participated in 2 online surveys and then convened a summit meeting. Published data and meeting abstracts from 2015 to 2019 were reviewed.

Findings: The MPWG members are optimistic about the future use of prognostic GEP testing to improve risk stratification and enhance clinical decision-making but acknowledge that current utility is limited by test performance in patients with stage I disease. Published studies of GEP testing have not evaluated results in the context of all relevant clinicopathologic factors or as predictors of regional nodal metastasis to replace sentinel lymph node biopsy (SLNB). The performance of GEP tests has generally been reported for small groups of patients representing particular tumor stages or in aggregate form, such that stage-specific performance cannot be ascertained, and without survival outcomes compared with data from the American Joint Committee on Cancer 8th edition melanoma staging system international database. There are significant challenges to performing clinical trials incorporating GEP testing with SLNB and adjuvant therapy. The MPWG members favor conducting retrospective studies that evaluate multiple GEP testing platforms on fully annotated archived samples before embarking on costly prospective studies and recommend avoiding routine use of GEP testing to direct patient management until prospective studies support their clinical utility.

Conclusions and relevance: More evidence is needed to support using GEP testing to inform recommendations regarding SLNB, intensity of follow-up or imaging surveillance, and postoperative adjuvant therapy. The MPWG recommends further research to assess the validity and clinical applicability of existing and emerging GEP tests. Decisions on performing GEP testing and patient management based on these results should only be made in the context of discussion of testing limitations with the patient or within a multidisciplinary group.

The incidence gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) has dramatically risen over the last three decades, probably due to the increased detection of asymptomatic lesions. The diagnostic work-up for patients with suspected GEP-NENs is based on conventional imaging, endoscopy, pathology, and functional imaging, including ⁶⁸Gallium-DOTATATE PET and ¹⁸F-FDG PET. The choice of the best treatment strategy should be based on the evaluation of tumor-related features and patient's characteristics. A conservative management, consisting of active surveillance or endoscopic resection, has been advocated for patients with small, incidentally discovered, nonfunctioning tumors without features of aggressiveness. On the other hand, surgery with lymphadenectomy, also with a minimally invasive approach, represents the gold standard for the curative treatment of localized disease. Moreover, surgical resection plays an important role also in the context of a multimodal treatment strategy for patients with advanced GEP-NENs. Finally, a wide range of medical therapies, comprising somatostatin analogues, peptide receptor radionuclide therapy, target therapies and several chemotherapy regimens, can be offered to patients with advanced GEP-NENs not amenable of surgical resection, according to the biological and molecular features of their disease.

Keywords: Active surveillance; Endoscopic resection; Gastroenteropancreatic neuroendocrine neoplasms; Surgery.

Impairment of natural killer (NK) cell activity is an important mechanism of tumor immunoevasion. We have previously shown that expression of granulin-epithelin precursor (GEP) in hepatocellular carcinoma (HCC) cells rendered the cells resistant to NK cell immunosurveillance. Here, we examined whether targeting GEP could rescue NK activity in HCC patients. The current study demonstrated that quantities and activities of NK cells were significantly lower in HCC patients compared with healthy individuals, and were negatively correlated with GEP levels in HCC cells. NK cells demonstrated enhanced expression of the stimulatory receptors natural-killer group 2, member D (NKG2D) and CD69, increased secretion of IFN-γ and perforin, and cytotoxicity against HCC cells upon GEP suppression. Opposite phenotypes of NK cells were observed when GEP was overexpressed in HCC cells. Importantly, GEP blockage by monoclonal antibody A23 restored NK activity in HCC patients and sensitized HCC cells to NK cytotoxicity. Furthermore, A23 induced NK-mediated antibody-dependent cell-mediated cytotoxicity against HCC. In summary, the activity of NK cells in HCC was impaired by GEP expression, which could be rescued by GEP antibody. This study provides new insight for treatments targeting GEP to boost NK activity in HCC patients.

BACKGROUND

Many changes have recently occurred in the practice of neuroendocrine tumour (NET) pathology. We therefore aimed to evaluate how pathologists have adapted their daily practice to the most recent international guidelines for diagnostic and prognostic evaluation.

METHODS

A 12-month prospective study (PRONET) was carried out among French pathologists between August 2010 and July 2011. Data were collected using an anonymous electronic case report form.

METHODS

Five hundred laboratories were invited, 149 accepted to participate, 80 were active and 59 provided eligible cases. A total of 1,340 cases were collected. The primary tumour was gastroenteropancreatic in 58.1% of cases and thoracic in 18.1%; it was from another site in 9.7%; 12.3% of cases were metastases of unknown origin. Pathological diagnosis was made from the examination of surgical samples in 58.1% of cases, biopsy specimens in 33.5%, endoscopic resections in 3.1% and cytological preparations in 4.2%. For the demonstration of the neuroendocrine nature of the tumour, chromogranin A and synaptophysin were tested in, respectively, 97.1 and 82.8% of cases. The differentiation status was definitely provided in 95.7% of cases. Mitotic count was attempted in 80.1% of cases and Ki67 index in 80.7%. In gastroenteropancreatic (GEP)-NETs, histological grading was available in 95.9% of the cases. WHO classification was available or feasible in 94.1% of GEP-NETs and 93.8% of thoracic NETs. TNM staging was performed according to International Union against Cancer in 74.8% of GEP-NETs and according to European Neuroendocrine Tumour Society in 55.6%.

CONCLUSIONS

The PRONET study shows that the current recommendations and diagnostic procedures are satisfactorily respected by most pathologists in daily practice.

Gastroenteropancreatic neuroendocrine neoplasms grade 3 (GEP-NENs G3) are rare tumors. These highly aggressive neoplasms are traditionally treated with platinum-based chemotherapy in combination with etoposide. Immune checkpoint proteins such as programmed cell death ligand (PD-L1) may have a role in different cancers allowing them escape the immune system and hence, progress. We aimed to investigate the immunohistochemical expression of PD-L1 in GEP-NEN G3 and evaluate its correlation to clinical parameters. In a cohort of 136 patients, 14 (10%) expressed PD-L1 immunoreactivity; four (3%) patients in the tumor cells and 10 (7%) had immunoreactive immune cells. PD-L1 expression did not correlate to clinical parameters, progression-free survival or overall survival. We conclude that PD-L1 expression is present only in a subset of GEP-NEN G3 patients. Further studies are needed to fully understand the role of PD-L1 in patients with GEP-NEN G3, including the future possibility for treatment with immune checkpoint inhibitors.

Somatostatin receptors (SSTRs) already act as important roles in gastroenteropancreatic neuroendocrine tumors (GEP-NETs) with high expression levels for prognosis predicting and octreotide LAR treatment purposes but less noticed in gastrointestinal stromal tumors (GISTs). Our study aims to fully evaluate the expression levels and prognostic values of SSTRs in GIST patients. For SSTRs expression detection, qPCR were used in 25 fresh GIST specimens, and then, 453 GIST samples (405 GISTs with operation only and 48 with imatinib adjuvant therapy after surgery) were collected for tissue microarrays (TMAs) construction and confirmed by immunohistochemistry (IHC). Clinicopathological data were confirmed by pathological diagnosis and clinical recorders, recurrence-free survivals (RFS) were evaluated in 453 GIST patients. With IHC performed, SSTR1 and SSTR2 present high positive proportion (81.9% and 87.6%) in 453 GISTs in our study, and positive expression rates of SSTR3, SSTR4 and SSTR5 are 56.1%, 8.8% and 47.2%, respectively. SSTR2 and SSTR5 negative expression are associated with decreased RFS when compared to positive cases by Kaplan-Meier survival analyses with log-rank test and univariate analysis in GISTs, furthermore, SSTR2 was an independent prognostic indicator for GISTs by multivariate analysis. In our study, detection of SSRT2 and SSTR5 expression helps to predict different prognosis in GIST patients. SSTR2 is a novel independent prognostic biomarker for GISTs. With high expression performance of SSTRs in GISTs, new therapeutic strategies such as octreotide or pasireotide LAR could be taken into consideration in selected advanced GIST patients.

Depression is a common mental health disorder and is the leading cause of disability worldwide. Gastrodia elata (G. elata) was demonstrated to exhibit a neuroprotective effect in the authors' previous study. The present study investigated the effect of polysaccharides from G. elata (GEP) on PC12 cell apoptosis induced by corticosterone (CORT) and its possible underlying mechanisms. PC12 cells were treated with 200 µM CORT in the absence or presence of different concentrations of GEP for 48 h. Then, cell viability was measured by CCK‑8 assay. The lactate dehydrogenase (LDH) leakage was quantified using an LDH assay kit. The apoptosis degree of the PC12 cells and the morphology was measured by DAPI staining. Subsequently, intracellular ROS level was detected by using DCFH‑DA method, the morphology staining of the endoplasmic reticulum in PC12 cells was determined using the cationic probe, and levels of five proteins involved in apoptosis, i.e., glucose‑regulated protein, 78k Da (GRP78), X‑box binding protein 1 (XBP‑1), growth arrest‑ and DNA damage‑inducible gene 153 (GADD153), caspase 9 and caspase 12 were determined by western blotting. The results demonstrated that treatment with 1,000 µg/ml GEP prior to 200 µM CORT exposure significantly protected the PC12 cells from CORT‑induced cell apoptosis, and reduced levels of LDH leakage and intracellular reactive oxygen species. In addition, pretreatment with GEP inhibited the activation of GRP78, X‑BP‑1, GADD153, caspase 9 and caspase 12. These findings suggested that GEP exhibited a neuroprotective effect against CORT‑induced apoptosis in PC12 cells, and the underlying molecular mechanisms were dependent on inhibition of the endoplasmic reticulum stress‑mediated pathway. This provides novel insight into the effect of GEP when used for the treatment of diseases of the nervous system.

A patient's response to immune checkpoint inhibitors (ICIs) is a complex quantitative trait, and determined by multiple intrinsic and extrinsic factors. Three currently FDA-approved predictive biomarkers (progra1mmed cell death ligand-1 (PD-L1); microsatellite instability (MSI); tumor mutational burden (TMB)) are routinely used for patient selection for ICI response in clinical practice. Although clinical utility of these biomarkers has been demonstrated in ample clinical trials, many variables involved in using these biomarkers have poised serious challenges in daily practice. Furthermore, the predicted responders by these three biomarkers only have a small percentage of overlap, suggesting that each biomarker captures different contributing factors to ICI response. Optimized use of currently FDA-approved biomarkers and development of a new generation of predictive biomarkers are urgently needed. In this review, we will first discuss three widely used FDA-approved predictive biomarkers and their optimal use. Secondly, we will review four novel gene signature biomarkers: T-cell inflamed gene expression profile (GEP), T-cell dysfunction and exclusion gene signature (TIDE), melanocytic plasticity signature (MPS) and B-cell focused gene signature. The GEP and TIDE have shown better predictive performance than PD-L1, and PD-L1 or TMB, respectively. The MPS is superior to PD-L1, TMB, and TIDE. The B-cell focused gene signature represents a previously unexplored predictive biomarker to ICI response. Thirdly, we will highlight two combined predictive biomarkers: TMB+GEP and MPS+TIDE. These integrated biomarkers showed improved predictive outcomes compared to a single predictor. Finally, we will present a potential nucleic acid biomarker signature, allowing DNA and RNA biomarkers to be analyzed in one assay. This comprehensive signature could represent a future direction of developing robust predictive biomarkers, particularly for the cold tumors, for ICI response.

Keywords: FDA-approved biomarkers; PD-1; TMB; immune checkpoint inhibitors; predictive biomarkers.

Purpose: In our study, tumor heterogeneity was evaluated using the parameters skewness and kurtosis on pretreatment Ga-68 DOTA-TATE PET/CT to assess therapy responses of lesions in patients with gastroenteropancreatic neuroendocrine tumors (GEP NETs) treated with peptide receptor radionuclide therapy (PRRT).

Method: We retrospectively studied the texture analysis with relatively simple first-order parameters skewness and kurtosis on pretreatment Ga-68 DOTA-TATE PET/CT from 22 patients (eight females, 14 males; with a mean age: 54 ± 11 years) with GEP NETs who were treated with 2-6 therapy cycles of Lu-177 DOTA-TATE. A total of 326 lesions of 22 patients were evaluated in terms of treatment response by Ga-68 DOTA-TATE PET/CT examination performed before and after treatment. Receiver-operating characteristic (ROC) curves were generated to assess skewness and kurtosis to discriminate between responder and nonresponder lesions.

Result: A total of 326 lesions of 22 patients were evaluated and 137 lesions responded partially or completely to the treatment, 189 lesions did not respond to treatment, remained stable or progressed. The skewness and kurtosis values of the lesions which did not respond to the PRRT were significantly higher than those with response to PRRT treatment (P < 0.001 and P = 0.004, respectively). However, ROC curves provided a moderate area under the curve value for skewness and a relatively low value for kurtosis (0.619 and 0.518, respectively).

Conclusion: Texture analysis using skewness and kurtosis of the lesions on pretreatment Ga-68 DOTA-TATE PET/CT was able to predict their responsiveness to PRRT.