Syöpälääkkeiden aiheuttaman pahoinvoinnin yksilöllinen hoito

Syöpälääkehoidon aiheuttama pahoinvointi ja oksentelu heikentävät yhä syöpäpotilaiden elämänlaatua. Pahoinvointi voidaan jakaa akuuttiin, viivästyneeseen, syöpälääkehoitoa ennakoivaan, hoitoon huonosti reagoivaan ja läpilyöntipahoinvointiin. Kaikilla näillä muodoilla arvellaan olevan erilainen syntymekanismi, ja siksi niiden hoidot ovat erilaiset. Akuutti pahoinvointi ilmaantuu 24 tunnin kuluessa syöpälääkehoidosta. Viivästynyt pahoinvointi alkaa 24 tunnin kuluttua syöpälääkehoidon jälkeen ja voi kestää jopa useita päiviä hoidon päätyttyä. Pahoinvointiriskiin vaikuttavat syöpälääkehoidon emetogeenisuus eli ominaisuus aiheuttaa pahoinvointia sekä potilaaseen liittyvät riskitekijät. Estohoidossa käytettäviä lääkkeitä ovat 5-HT3- ja NK1-reseptorien salpaajat sekä deksametasoni, olantsapiini ja metoklopramidi. Syöpähoitojen aiheuttaman pahoinvoinnin hoidon tavoite eli pahoinvoinnin ja oksentelun täydellinen ehkäisy voidaan saavuttaa räätälöimällä estolääkitys yksilöllisesti.publishedVersionPeer reviewe

Rintasyövän neoadjuvanttihoidon toteutuminen ja tulokset

publishedVersionPeer reviewe

Dosentit : yliopiston merkittävä voimavara

“Dosentit - yliopiston merkittävä voimavara” -teos kerää yksiin kansiin Tampereen Dosenttiyhdistyksen järjestämän Dosenttien päivän 20.4.2023 mielenkiintoiset ja ajankohtaiset luennot. Kaikki kyseiset dosentit ovat saaneet dosentin arvon Tampereen yliopistosta. Tekstit ovat kansantajuisia ja suurelle yleisölle suunnattuja

Detecting Activation of Ribosomal Protein S6 Kinase by Complementary DNA and Tissue Microarray Analysis

Background: Studies by comparative genomic hybridization (CGH) have shown that chromosomal region 17q23 is amplified in up to 20% of primary breast cancers. We used microarray analyses to measure the expression levels of genes in this region and to explore their prognostic importance. Methods: A microarray that contained 4209 complementary DNA (cDNA) clones was used to identify genes that are overexpressed in the MCF-7 breast cancer cell line as compared with normal mammary tissue. Fluorescence in situ hybridization was used to analyze the copy number of one overexpressed gene, ribosomal protein S6 kinase (S6K), and to localize it to the 17q23 region. Northern and western blot analyses were used to measure S6K gene and protein expression, and an enzymatic assay was used to measure S6K activity. Tumor tissue microarray analysis was used to study amplification of S6K and the HER-2 oncogene, another 17q-linked gene, and the relationship between amplification and prognosis was analyzed. The Kaplan-Meier method was used for data analysis, and the log-rank test was used for statistical analysis. All P values are two-sided. Results: S6K was amplified and highly overexpressed in MCF-7 cells relative to normal mammary epithelium, and protein expression and enzyme activity were increased. S6K was amplified in 59 (8.8%) of 668 primary breast tumors, and a statistically significant association between amplification and poor prognosis (P = .0021) was observed. Amplification of both S6K and HER-2 implied particularly poor survival (P = .0001). Conclusions: The combination of CGH information with cDNA and tissue microarray analyses can be used to identify amplified and overexpressed genes and to evaluate the clinical implications of such genes and genomic rearrangements. S6K is likely to be one of the genes at 17q23 that is amplified during oncogenesis and may adversely affect the prognosis of patients with this amplificatio

Improved risk prediction of chemotherapy-induced neutropenia-model development and validation with real-world data

Background The existing risk prediction models for chemotherapy-induced febrile neutropenia (FN) do not necessarily apply to real-life patients in different healthcare systems and the external validation of these models are often lacking. Our study evaluates whether a machine learning-based risk prediction model could outperform the previously introduced models, especially when validated against real-world patient data from another institution not used for model training.Methods Using Turku University Hospital electronic medical records, we identified all patients who received chemotherapy for non-hematological cancer between the years 2010 and 2017 (N = 5879). An experimental surrogate endpoint was first-cycle neutropenic infection (NI), defined as grade IV neutropenia with serum C-reactive protein >10 mg/l. For predicting the risk of NI, a penalized regression model (Lasso) was developed. The model was externally validated in an independent dataset (N = 4594) from Tampere University Hospital.Results Lasso model accurately predicted NI risk with good accuracy (AUROC 0.84). In the validation cohort, the Lasso model outperformed two previously introduced, widely approved models, with AUROC 0.75. The variables selected by Lasso included granulocyte colony-stimulating factor (G-CSF) use, cancer type, pre-treatment neutrophil and thrombocyte count, intravenous treatment regimen, and the planned dose intensity. The same model predicted also FN, with AUROC 0.77, supporting the validity of NI as an endpoint.Conclusions Our study demonstrates that real-world NI risk prediction can be improved with machine learning and that every difference in patient or treatment characteristics can have a significant impact on model performance. Here we outline a novel, externally validated approach which may hold potential to facilitate more targeted use of G-CSFs in the future.</p

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Gene Amplification at 17q23 in breast cancer: Molecular Cytogetic and Microarray studies

Rintasyöpä on naisten ylivoimaisesti yleisin syöpä Suomessa. Vuosittain Suomessa diagnosoidaan yli 3300 uutta rintasyöpätapausta. Rintasyövän syntyyn johtavat muutokset geenien toiminnassa. Suurin osa geenivirheista on elintapojen, ymparistötekijöiden ja vanhenemisen myötä syntyviä muutoksia rintarauhassolujen geenien rakenteessa ja toiminnassa. Valtaosa syövän geenimuutoksista ei ole periytyviä. Vasta pieni osa rintasyövän geenivirheistä on tunnistettu ja vielä vähemmän tunnetaan näiden geenivirheiden kliinistä merkitystä. Ihmisen perimän emäsjärjestyksen selvittäminen (human genome program) on jättimäinen tiedeprojekti, jonka ensimmäinen vaihe valmistuu kesään 2000 mennessä. Tällöin opimme tuntemaan kaikki ne arviolta n. 150 000 geeniä, jotka säätelevat ihmisen kasvua, kehitystä, ja kaikkia solujen toimintoja. Ihmisgenomin kartoitus on ratkaisevasti muuttamassa biolääketieteellisen tutkimuksen mahdollisuuksia. Kaikkien geenien tunnistaminen on ensimmäinen vaihe, tämän jälkeen täytyy oppia ymmärtämään kunkin geenin biologinen merkitys, ja mahdollinen osuus tautien synnyssä. Käänteentekevä menetelmä tässä suhteessa on DNA-siruteknologia, jonka avulla kymmenien tuhansien geenien toiminta voidaan määrittää samanaikaisesti. Niinpä esim. syövässä poikkeavasti toimivat geenit voidaan tunnistaa jopa 10 000-kertaa aiempaa nopeammin. Jotta kertyvää valtavaa tietomäärää voitaisiin nopeasti hyödyntää kliinisten sovellutusten tutkimuksessa, tarvitaan myös soveltavan ja kliinisen tutkimuksen puolella uusia m! enetelmiä ja lähestymistapoja. Tässä tutkimuksessa kehitimme uuden menetelmän, kudossiruteknologian, joka mahdollistaa tuhansien potilasnäytteiden analysoinnin samanaikaisesti ja nopeasti. DNA-siru ja kudossirutekniikat ovat ratkaisevasti nopeuttaneet geenilöydösten ja niiden kliinisen merkityksen tutkimusta. Tätä tutkimusstrategiaa sovelsimme menestyksellisesti uuden rintasyövässä aktivoituvan geenin, ribosomaalisen S6 kinaasin (S6K) löytämiseen, ja sen kliinisen merkityksen tutkimukseen. Potilailla, joilla todettiin S6K geenin aktivoituminen, oli selkeästi muita huonompi ennuste. Tutkimuksessa tunnistettiin myos useita muita rintasyövän syntyyn ja leviämiseen liittyviä geenejä. Uusien syöpägeenien tunnistaminen on ensiarvoisen tärkeää taudin syntymekanismien ymmärtämiseksi sekä diagnostisten ja hoitovastetta ennakoivien laboratoriotestien kehittämiseksi. Syöpä- ja normaalikudoksen väliset erot geenien toiminnassa muodostavat myös lähtökohdan uusien syöpälääkkeiden kehittämiselle. Tässä tutkimuksessa saadut tulokset saattavat siten tulevaisuudessa parantaa rintasyöpäpotilaiden hoidon suunnittelua, hoidon toteutusta ja sen tehon arviointia.Cancer is a disease that results from a series of molecular genetic events involving activation of oncogenes, inactivation of tumor-suppressor genes and dysfunction of proteins encoded by genes involved in DNA repair and maintenance of genomic stability. In breast cancer, the predominant mechanism of oncogene activation is gene amplification. Studies by comparative genomic hybridization have shown that chromosomal region 17q22-q24 is one of the most often amplified chromosomal regions in breast cancer. However, no currently known oncogenes are located at 17q22-q24 suggesting that this region may harbor previously unknown genes that are important in breast cancer progression. The aim of this study was to develop and apply molecular cytogenetic genome scanning and microarray techniques for the characterization of the 17q22-q24 amplification in breast cancer as well as to analyze its clinical significance. As an initial characterization of the 17q22-24 amplification, copy number profiles along 17q were constructed using fluorescence in situ hybridization (FISH) with physically mapped 17q probes. FISH showed that at least two separate regions at 17q23 undergo high-level amplification in breast cancer. The distal region was amplified independently of ERBB2 and was chosen for further study. An approximately 4 megabase (Mb) contig containing 64 large insert size clones and 77 STSs was constructed. 101 transcripts and 6 known genes (RAD51C, S6K, PAT1, NACA, SIGMA1B and TBX2) were mapped to this region. Four of them (RAD51C, S6K, PAT1, and TBX2) were shown to be highly amplified and overexpressed in breast cancer cell lines, indicating that they might have a role as a target for the 17q23 amplification. Simultaneous screening of expression levels of 4209 genes by cDNA microarrays in cell lines with high-level amplification at 17q23 identified the ribosomal protein S6 kinase (S6K) as the most highly upregulated gene of all the genes tested. S6K was systematically overexpressed in all 17q23 amplified breast cancer cell lines. It codes for a critical regulator of G1 to S-phase transition and therefore represents an attractive target gene to be amplified in breast cancer. In addition, RT-PCR screening of transcripts mapped to the amplified region at 17q23 pinpointed a highly overexpressed EST. The corresponding gene (MB1) was cloned, and sequence analysis showed no homology to any other genes. A new high-throughput method, tumor tissue microarray ("tissue chip") was developed to facilitate rapid molecular profiling of very large numbers of specimens in a single experiment. Tissue microarrays are constructed by bringing minute cylindrical tissue samples (diameter 0.6 mm) from hundreds of different tumors into a single paraffin block in an array format. Sections cut from this tissue microarray block can then be applied in the analysis of molecular alterations at the DNA, RNA or protein level, using e.g. in situ hybridization or immunohistochemistry. To investigate the involvement of the amplified and overexpressed genes in vivo, FISH analysis of a tissue microarray containing 372 primary breast cancers was used. S6K, PAT1, and TBX2 were often co-amplified and involved in about 10% of tumors, whereas RAD51C amplification was only seen in 3% of the tumors. The clinical significance of S6K amplification was studied using a tissue array for which prognostic information on the patients was available. A clear association between amplification and poor prognosis of the patients was observed (p=0.002). The fact that S6K, PAT1, and TBX2 were frequently co-amplified suggests that similar prognostic association could be observed with the other genes as well. Furthermore, co-amplification of S6K and ERBB2 genes implied a particularly poor survival. In summary, our findings indicate that the frequent amplification of 17q23 in breast cancer leads to upregulation of multiple genes (RAD51C, S6K, PAT1, TBX2 and novel gene MB1) suggesting that their simultaneous activation may contribute to the initiation and progression of breast cancer. These genes represent candidate targets for specific molecular therapies