Emerging role of signal transducer and activator of transcription 3 (STAT3) in pituitary adenomas

Update on Current Evidence for the Diagnosis and Management of Nonfunctioning Pituitary Neuroendocrine Tumors

Pituitary neuroendocrine tumors (PitNETs) are the third most frequently diagnosed intracranial tumors, with nonfunctioning PitNETs (nfPitNETs) accounting for 30% of all pituitary tumors and representing the most common type of macroPitNETs. NfPitNETs are usually benign tumors with no evidence of hormone oversecretion except for hyperprolactinemia secondary to pituitary stalk compression. Due to this, they do not typically present with clinical syndromes like acromegaly, Cushing's disease or hyperthyroidism and instead are identified incidentally on imaging or from symptoms of mass effects (headache, vision changes, apoplexy). With the lack of effective medical interventions, first-line treatment is transsphenoidal surgical resection, however, nfPitNETs often have supra- or parasellar extension, and total resection of the tumor is often not possible, resulting in residual tumor regrowth or reoccurrence. While functional PitNETs can be easily followed for recurrence using hormonal biomarkers, there is no similar parameter to predict recurrence in nfPitNETs, hence delaying early recognition and timely management. Therefore, there is a need to identify prognostic biomarkers that can be used for patient surveillance and as therapeutic targets. This review focuses on summarizing the current evidence on nfPitNETs, with a special focus on potential new biomarkers and therapeutics.

Estimation of bloodstain deposition time within a 24-h day-night cycle with rhythmic mRNA based on a machine learning algorithm

Estimating the time that bloodstains are left at a crime scene can provide invaluable evidence for law enforcement investigations, including determining the time of the crime, linking the perpetrator to the crime scene, narrowing the pool of possible suspects, and verifying witness statements. There have been some attempts to estimate the time since deposition of bloodstains, i.e., how much time has passed since the bloodstain was left at a crime scene. However, most studies focus on the time interval of days. As far as we know, previous study have been conducted to estimate the deposition time of blood within a 24-h day-night cycle. To date, there is a lack of studies on whether rhythmic mRNA of blood is suitable for bloodstain samples. In this study, we estimated the bloodstain deposition time within a 24-h day-night cycle based on the expression of messenger RNAs (mRNAs) by real-time quantitative polymerase chain reaction. Bloodstain samples were prepared from eight individuals at eight time points under real and uncontrolled conditions. Four mRNAs expressed rhythmically and were used to construct a regression model using the k-nearest neighbor (KNN) algorithm, resulting in a mean absolute error of 3.92 h. Overall, using the rhythmic mRNAs, a machine learning model was developed which has allowed us to predict the deposition time of bloodstains within the 24-h day-night cycle in East Asian populations. This study demonstrates that mRNA biomarkers can be used to estimate the bloodstain deposition time within a 24-h period. Furthermore, rhythmic mRNA biomarkers provide a potential method and perspective for estimating the deposition time of forensic traces in forensic investigation. Case samples in forensic analysis are usually limited or degraded, so the stability and sensitivity of rhythmic biomarkers need to be further investigated.

The hallmarks of cancer… in pituitary tumors?

Over 20 years ago, Hanahan and Weinberg published a seminal review that addressed the biological processes that underly malignant transformation. This classical review, along with two revisions published in 2011 and 2022, has remain a classic of the oncology literature. Since many of the addressed biological processes may apply to non-malignant tumorigenesis, we evaluated to what extent these hallmarks pertain to the development of pituitary adenomas.Some of the biological processes analyzed in this review include genome instability generated by somatic USP8 and GNAS mutations in Cushing's diseases and acromegaly respectively; non-mutational epigenetic reprograming through changes in methylation; induction of angiogenesis through alterations of VEGF gene expression; promotion of proliferative signals mediated by EGFR; evasion of growth suppression by disrupting cyclin dependent kinase inhibitors; avoidance of immune destruction; and the promotion of inflammation mediated by alteration of gene expression of immune check points. We also elaborate further on the existence of oncogene induced senescence in pituitary tumors. We conclude that a better understanding of these processes can help us dilucidated why pituitary tumors are so resistant to malignant transformation and can potentially contribute to the development of novel anticancer treatments.

The kinome, cyclins and cyclin-dependent kinases of pituitary adenomas, a look into the gene expression profile among tumors from different lineages

Background

Pituitary adenomas (PA) are the second most common intracranial tumors and are classified according to hormone they produce, and the transcription factors they express. The majority of PA occur sporadically, and their molecular pathogenesis is incompletely understood.

Methods

Here we performed transcriptome and proteome analysis of tumors derived from POU1F1 (GH-, TSH-, and PRL-tumors, N = 16), NR5A1 (gonadotropes and null cells adenomas, n = 17) and TBX19 (ACTH-tumors, n = 6) lineages as well as from silent ACTH-tumors (n = 3) to determine expression of kinases, cyclins, CDKs and CDK inhibitors.

Results

The expression profiles of genes encoding kinases were distinctive for each of the three PA lineage: NR5A1-derived tumors showed upregulation of ETNK2 and PIK3C2G and alterations in MAPK, ErbB and RAS signaling, POU1F1-derived adenomas showed upregulation of PIP5K1B and NEK10 and alterations in phosphatidylinositol, insulin and phospholipase D signaling pathways and TBX19-derived adenomas showed upregulation of MERTK and STK17B and alterations in VEGFA-VEGFR, EGF-EGFR and Insulin signaling pathways. In contrast, the expression of the different genes encoding cyclins, CDK and CDK inhibitors among NR5A1-, POU1F1- and TBX19-adenomas showed only subtle differences. CDK9 and CDK18 were upregulated in NR5A1-adenomas, whereas CDK4 and CDK7 were upregulated in POUF1-adenomas.

Conclusions

The kinome of PA clusters these lesions into three distinct groups according to the transcription factor that drives their terminal differentiation. And these complexes could be harnessed as molecular therapy targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01206-y.