We use cookies to enhance the usability of our website. If you continue, we'll assume that you are happy to receive all cookies. More information. Don't show this again.
GSTT2
HPA
RESOURCES
  • TISSUE
  • BRAIN
  • SINGLE CELL
  • SUBCELLULAR
  • CANCER
  • BLOOD
  • CELL LINE
  • STRUCTURE & INTERACTION
ABOUT
  • INTRODUCTION
  • HISTORY
  • ORGANIZATION
  • PUBLICATIONS
  • ANTIBODY SUBMISSION
  • ANTIBODY AVAILABILITY
  • ACKNOWLEDGMENTS
  • CONTACT
NEWS
  • NEWS ARTICLES
  • PRESS ROOM
LEARN
  • DICTIONARY
  • PROTEIN CLASSES
  • PROTEIN EVIDENCE
  • METHODS
  • EDUCATIONAL VIDEOS
DATA
  • DOWNLOADABLE DATA
  • PUBLICATION DATA
  • RELEASE HISTORY
HELP
  • ANTIBODY VALIDATION
  • ASSAYS & ANNOTATION
  • DISCLAIMER
  • HELP & FAQ
  • PRIVACY STATEMENT
  • LICENCE & CITATION
Fields »
Search result

Field
Term
Gene name
Class
Subclass
Class
Keyword
Chromosome
External id
Tissue
Cell type
Expression
Antibody panel
Tissue
Main location
Patient ID
Annotation
Tissue
Category
Tau score
Cluster
Reliability
Brain region
Category
Tau score
Brain region
Category
Tau score
Brain region
Category
Tau score
Cluster
Reliability
Tissue
Cell type
Enrichment
Cell type
Category
Tau score
Cell type
Category
Tau score
Cell type
Category
Tau score
Cell lineage
Category
Tau score
Cluster
Cluster
Location
Searches
Location
Cell line
Class
Type
Phase
Reliability
Cancer
Prognosis
Cancer
Category
Cancer
Category
Tau score
Cluster
Variants
Interacting gene (ensg_id)
Type
Number of interactions
Pathway
Category
Score
Score
Score
Validation
Validation
Validation
Validation
Antibodies
Data type
Column


  • SUMMARY

  • TISSUE

  • BRAIN

  • SINGLE CELL

  • SUBCELL

  • CANCER

  • BLOOD

  • CELL LINE

  • STRUCT & INT

  • GSTT2
CANCER LIVER CANCER Show tissue menu
BREAST CANCER CARCINOID CERVICAL CANCER COLORECTAL CANCER ENDOMETRIAL CANCER GLIOMA HEAD AND NECK CANCER LIVER CANCER LUNG CANCER LYMPHOMA
MELANOMA OVARIAN CANCER PANCREATIC CANCER PROSTATE CANCER RENAL CANCER SKIN CANCER STOMACH CANCER TESTIS CANCER THYROID CANCER UROTHELIAL CANCER
LIHC TCGA LIHC VALIDATION PROTEIN LIHC CPTAC PROTEIN EXPRESSION
ANTIBODIES
AND
VALIDATION
Dictionary
Liver cancer
Human cancer
Liver hepatocellular carcinoma
LIVER HEPATOCELLULAR CARCINOMA (TCGA) - Interactive survival scatter ploti

The Survival Scatter plot shows the clinical status (i.e. dead or alive) for all individuals in the patient cohort, based on the same data that underlies the corresponding Kaplan-Meier plots. Patients that are alive at last time for follow-up are shown in blue and patients who have died during the study are shown in red.

The x-axis shows the expression levels (FPKM) of the investigated gene in the tumor tissue at the time of diagnosis. The y-axis shows the follow-up time after diagnosis (years). Both axes are complimented with kernel density curves demonstrating the data density over the axes. The top density plot shows the expression levels (FPKM) distribution among dead (red) and alive patients (blue). The right density plot shows the data density of the survived years of dead patients with high and low expression levels respectively, stratified using the cutoff indicated by the vertical dashed line through the Survival Scatter plot. This cutoff is automatically defined based on the FPKM cutoff that minimizes the p-score. The cutoff can be changed by dragging the vertical line or by entering a cutoff value in the square labeled "Current cut-off".

Under the Survival Scatter plot the p-score landscape (black curve; left axis) is shown together with dead median separation (red curve; right axis). Dead median separation is the difference in median mRNA expression between patients who have died with high and low expression, respectively. It is calculated as follows: median FPKM expression of dead patients with high expression - median FPKM expression of dead patients with low expression. This is intended to aid the user in visually exploring custom cutoffs and the associated p-scores and dead median separation.

Individual patient data is displayed and can be filtered by clicking on one or more of the category buttons on the top of the page. Categories describing expression level and patient information include: high, low, alive, dead, female, male and tumor stages. The scale of the x-axis can be toggled between linear and log-scale by clicking on the "x log" button. Mouse-over function shows TCGA ID, patient information and mRNA expression (FPKM) for each patient.

& Survival analysisi

Kaplan-Meier plots summarize results from analysis of correlation between mRNA expression level and patient survival. Patients were divided based on level of expression into one of the two groups "low" (under cut off) or "high" (over cut off). X-axis shows time for survival (years) and y-axis shows the probability of survival, where 1.0 corresponds to 100 percent.

  Survival analysis data not available.
LIVER HEPATOCELLULAR CARCINOMA (VALIDATION) - Interactive survival scatter ploti

The Survival Scatter plot shows the clinical status (i.e. dead or alive) for all individuals in the patient cohort, based on the same data that underlies the corresponding Kaplan-Meier plots. Patients that are alive at last time for follow-up are shown in blue and patients who have died during the study are shown in red.

The x-axis shows the expression levels (FPKM) of the investigated gene in the tumor tissue at the time of diagnosis. The y-axis shows the follow-up time after diagnosis (years). Both axes are complimented with kernel density curves demonstrating the data density over the axes. The top density plot shows the expression levels (FPKM) distribution among dead (red) and alive patients (blue). The right density plot shows the data density of the survived years of dead patients with high and low expression levels respectively, stratified using the cutoff indicated by the vertical dashed line through the Survival Scatter plot. This cutoff is automatically defined based on the FPKM cutoff that minimizes the p-score. The cutoff can be changed by dragging the vertical line or by entering a cutoff value in the square labeled "Current cut-off".

Under the Survival Scatter plot the p-score landscape (black curve; left axis) is shown together with dead median separation (red curve; right axis). Dead median separation is the difference in median mRNA expression between patients who have died with high and low expression, respectively. It is calculated as follows: median FPKM expression of dead patients with high expression - median FPKM expression of dead patients with low expression. This is intended to aid the user in visually exploring custom cutoffs and the associated p-scores and dead median separation.

Individual patient data is displayed and can be filtered by clicking on one or more of the category buttons on the top of the page. Categories describing expression level and patient information include: high, low, alive, dead, female, male and tumor stages. The scale of the x-axis can be toggled between linear and log-scale by clicking on the "x log" button. Mouse-over function shows TCGA ID, patient information and mRNA expression (FPKM) for each patient.

& Survival analysisi

Kaplan-Meier plots summarize results from analysis of correlation between mRNA expression level and patient survival. Patients were divided based on level of expression into one of the two groups "low" (under cut off) or "high" (over cut off). X-axis shows time for survival (years) and y-axis shows the probability of survival, where 1.0 corresponds to 100 percent.

  Survival analysis data not available.
LIVER HEPATOCELLULAR CARCINOMA - Protein relative expression (CPTAC)
Number of samples 330
Samples
Sample ID Sample type nRPX
744 Normal 2.1
298 Normal 1.9
487 Tumor 1.7
728 Normal 1.7
342 Normal 1.6
465 Tumor 1.6
818 Normal 1.6
648 Normal 1.5
482 Normal 1.5
981 Tumor 1.4
196 Normal 1.4
392 Normal 1.3
462 Normal 1.3
746 Normal 1.3
488 Normal 1.3
445 Tumor 1.2
745 Tumor 1.2
313 Tumor 1.2
866 Normal 1.2
355 Tumor 1.2
523 Tumor 1.2
356 Normal 1.1
964 Normal 1.1
261 Tumor 1.1
146 Normal 1.1
982 Normal 1.1
882 Normal 1.0
227 Tumor 1.0
642 Normal 1.0
148 Normal 1.0
922 Normal 1.0
358 Normal 1.0
353 Tumor 1.0
448 Normal 0.9
1032 Normal 0.9
647 Tumor 0.9
354 Normal 0.9
142 Normal 0.9
862 Normal 0.9
132 Normal 0.9
423 Tumor 0.9
727 Tumor 0.8
376 Normal 0.8
664 Normal 0.8
714 Normal 0.8
564 Normal 0.8
756 Normal 0.8
755 Tumor 0.8
1026 Normal 0.8
968 Normal 0.8
742 Normal 0.8
111 Normal 0.8
145 Tumor 0.7
452 Normal 0.7
357 Tumor 0.7
1027 Tumor 0.7
456 Normal 0.7
883 Tumor 0.7
498 Normal 0.7
172 Normal 0.7
466 Normal 0.7
222 Normal 0.6
428 Normal 0.6
813 Tumor 0.6
1016 Normal 0.6
984 Normal 0.6
914 Normal 0.6
267 Tumor 0.6
314 Normal 0.6
262 Normal 0.6
884 Normal 0.6
1044 Normal 0.6
696 Normal 0.6
977 Tumor 0.6
1014 Normal 0.6
214 Normal 0.6
572 Normal 0.5
954 Normal 0.5
484 Normal 0.5
468 Normal 0.5
424 Normal 0.5
444 Normal 0.5
232 Normal 0.5
162 Normal 0.5
858 Normal 0.5
1042 Normal 0.5
1043 Tumor 0.5
524 Normal 0.5
672 Normal 0.5
966 Normal 0.5
666 Normal 0.5
384 Normal 0.5
546 Normal 0.5
958 Normal 0.5
716 Normal 0.5
386 Normal 0.4
913 Tumor 0.4
558 Normal 0.4
141 Tumor 0.4
494 Normal 0.4
278 Normal 0.4
446 Normal 0.4
272 Normal 0.4
228 Normal 0.4
944 Normal 0.4
686 Normal 0.4
114 Normal 0.4
126 Normal 0.4
814 Normal 0.4
161 Tumor 0.3
481 Tumor 0.3
912 Normal 0.3
937 Tumor 0.3
513 Tumor 0.3
368 Normal 0.3
957 Tumor 0.3
224 Normal 0.3
192 Normal 0.3
286 Normal 0.3
926 Normal 0.3
191 Tumor 0.3
195 Tumor 0.3
777 Tumor 0.3
534 Normal 0.3
364 Normal 0.3
297 Tumor 0.3
785 Tumor 0.3
861 Tumor 0.3
124 Normal 0.2
878 Normal 0.2
786 Normal 0.2
1022 Normal 0.2
554 Normal 0.2
365 Tumor 0.2
268 Normal 0.2
698 Normal 0.2
953 Tumor 0.2
443 Tumor 0.2
571 Tumor 0.2
538 Normal 0.2
361 Tumor 0.2
478 Normal 0.2
223 Tumor 0.2
695 Tumor 0.2
362 Normal 0.1
1041 Tumor 0.1
187 Tumor 0.1
852 Normal 0.1
778 Normal 0.1
125 Tumor 0.1
352 Normal 0.1
284 Normal 0.1
528 Normal 0.1
414 Normal 0.0
366 Normal 0.0
328 Normal 0.0
536 Normal 0.0
416 Normal 0.0
492 Normal 0.0
514 Normal 0.0
518 Normal 0.0
516 Normal 0.0
447 Tumor -0.1
136 Normal -0.1
915 Tumor -0.1
978 Normal -0.2
135 Tumor -0.2
938 Normal -0.2
983 Tumor -0.2
212 Normal -0.2
967 Tumor -0.2
477 Tumor -0.2
472 Normal -0.2
636 Normal -0.2
868 Normal -0.3
436 Normal -0.3
341 Tumor -0.3
663 Tumor -0.3
461 Tumor -0.3
963 Tumor -0.3
1015 Tumor -0.3
112 Tumor -0.4
277 Tumor -0.4
491 Tumor -0.4
422 Normal -0.4
824 Normal -0.4
916 Normal -0.4
1046 Normal -0.4
545 Tumor -0.4
952 Normal -0.4
434 Normal -0.4
455 Tumor -0.4
865 Tumor -0.5
877 Tumor -0.5
535 Tumor -0.5
881 Tumor -0.5
188 Normal -0.5
497 Tumor -0.6
332 Normal -0.6
1028 Normal -0.6
113 Tumor -0.6
415 Tumor -0.6
851 Tumor -0.6
956 Normal -0.7
363 Tumor -0.7
383 Tumor -0.7
976 Normal -0.7
344 Normal -0.7
517 Tumor -0.7
537 Tumor -0.7
943 Tumor -0.7
618 Normal -0.7
258 Normal -0.7
421 Tumor -0.8
385 Tumor -0.8
1025 Tumor -0.8
138 Normal -0.8
1013 Tumor -0.8
467 Tumor -0.8
213 Tumor -0.8
563 Tumor -0.8
955 Tumor -0.8
697 Tumor -0.8
367 Tumor -0.9
312 Normal -0.9
426 Normal -0.9
391 Tumor -0.9
131 Tumor -0.9
1045 Tumor -0.9
526 Normal -0.9
327 Tumor -0.9
257 Tumor -0.9
553 Tumor -0.9
1031 Tumor -0.9
665 Tumor -0.9
533 Tumor -0.9
388 Normal -1.0
743 Tumor -1.0
331 Tumor -1.0
641 Tumor -1.0
857 Tumor -1.0
483 Tumor -1.0
343 Tumor -1.0
137 Tumor -1.0
186 Normal -1.0
662 Normal -1.0
147 Tumor -1.0
464 Normal -1.1
393 Tumor -1.1
474 Normal -1.2
218 Normal -1.2
433 Tumor -1.2
427 Tumor -1.2
715 Tumor -1.2
283 Tumor -1.2
394 Normal -1.2
375 Tumor -1.2
413 Tumor -1.2
412 Normal -1.2
671 Tumor -1.2
351 Tumor -1.2
285 Tumor -1.3
211 Tumor -1.3
217 Tumor -1.3
713 Tumor -1.3
527 Tumor -1.3
311 Tumor -1.3
817 Tumor -1.3
723 Tumor -1.3
965 Tumor -1.3
975 Tumor -1.3
396 Normal -1.3
741 Tumor -1.3
432 Normal -1.3
271 Tumor -1.3
493 Tumor -1.4
616 Normal -1.4
451 Tumor -1.4
738 Normal -1.4
463 Tumor -1.4
615 Tumor -1.4
722 Normal -1.4
221 Tumor -1.4
411 Tumor -1.4
128 Normal -1.4
127 Tumor -1.5
661 Tumor -1.5
171 Tumor -1.5
635 Tumor -1.5
863 Tumor -1.5
525 Tumor -1.5
737 Tumor -1.6
185 Tumor -1.6
874 Normal -1.6
574 Normal -1.6
471 Tumor -1.6
628 Normal -1.6
925 Tumor -1.7
864 Normal -1.7
911 Tumor -1.7
816 Normal -1.7
473 Tumor -1.7
721 Tumor -1.7
617 Tumor -1.7
387 Tumor -1.7
123 Tumor -1.7
395 Tumor -1.7
568 Normal -1.7
685 Tumor -1.7
515 Tumor -1.7
231 Tumor -1.7
873 Tumor -1.8
431 Tumor -1.8
425 Tumor -1.8
921 Tumor -1.8
815 Tumor -1.8
924 Normal -1.9
867 Tumor -1.9
435 Tumor -1.9
557 Tumor -1.9
823 Tumor -1.9
627 Tumor -2.0
724 Normal -2.0
1021 Tumor -2.0
567 Tumor -2.0
951 Tumor -2.1
923 Tumor -2.1
918 Normal -2.1
917 Tumor -2.3
573 Tumor -2.4
Show allShow less
LIVER CANCER - Protein expressioni

A mouse-over function shows sample information and annotation data. Click on an image to view it in a full screen mode. Samples can be filtered based on level of antibody staining by selecting one or several of the following categories: high, medium, low and not detected. The assay and annotation is described here.

Note that samples used for immunohistochemistry by the Human Protein Atlas do not correspond to samples in the TCGA dataset.

 

Antibody stainingi

Antibody staining in the annotated cell types in the current human tissue is reported as not detected, low, medium, or high, based on conventional immunohistochemistry profiling in selected tissues. This score is based on the combination of the staining intensity and fraction of stained cells.

Each image is clickable and will lead to virtual microscopy that enables deeper exploration of all samples and also displays staining intensity scores, fraction scores and subcellular localization as well as patient and tissue information for each sample.


Antibody HPA000750
 Staining
  High
  Medium
  Low
  Not detected
 Intensity
  Strong
  Moderate
  Weak
  Negative
 Quantity
  >75%
  75%-25%
  <25%
  None
 Location
  Nuclear
  Cytoplasmic/membranous
  Cytoplasmic/membranous,nuclear
  None
Carcinoma, Hepatocellular, NOS
Cholangiocarcinoma

Contact

  • NEWS ARTICLES
  • PRESS ROOM

The Project

  • INTRODUCTION
  • ORGANIZATION
  • PUBLICATIONS

The Human Protein Atlas

  • DOWNLOADABLE DATA
  • LICENCE & CITATION
  • HELP & FAQ
The Human Protein Atlas project is funded
by the Knut & Alice Wallenberg Foundation.


contact@proteinatlas.org